{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}U:\Krypteret u-drev\Papers\Paper 1 - Disentangling\Submission_to_BJPS_final_fall_2019\Dofiles_and_data\Log_experiments.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}21 Nov 2019, 15:33:42

{com}. do "C:\Users\AU550446\AppData\Local\Temp\STD726c_000000.tmp"
{txt}
{com}. 
. clear all
{res}{txt}
{com}. use "U:\Krypteret u-drev\Papers\Paper 1 - Disentangling\Submission_to_BJPS_final_fall_2019\Dofiles_and_data\Data_from_experiments.dta"
{txt}
{com}. 
. ***********************************************
. **Creating indeces and other needed variables**
. ***********************************************
. 
. *creating dummy for party ID*
. gen Dem0Rep1 = .
{txt}(4,335 missing values generated)

{com}. replace Dem0Rep1 = 0 if partyid == 5 | partyid == 6 | partyid == 7
{txt}(2,182 real changes made)

{com}. replace Dem0Rep1 = 1 if partyid == 3 | partyid == 2 | partyid == 1
{txt}(1,303 real changes made)

{com}. gen PID_undecided_equal_4 = partyid
{txt}
{com}. replace PID_undecided_equal_4 = 4 if partyid == 8 | partyid == 9
{txt}(202 real changes made)

{com}. 
. *creating interaction terms manually*
. gen civ_party = Dem0Rep1 * civility
{txt}(1,348 missing values generated)

{com}. gen pol_party = Dem0Rep1 * low_or_high
{txt}(2,352 missing values generated)

{com}. gen civ_pol = civility * low_or_high
{txt}(1,845 missing values generated)

{com}. gen civ_pol_party = civility * low_or_high * Dem0Rep1
{txt}(2,352 missing values generated)

{com}. 
. *creating index for trust*
. gen first_trust = (trust1 - 1)/3*(-1)+1 if trust1 != 5
{txt}(265 missing values generated)

{com}. gen second_trust = (trust2 - 1)/8*(-1)+1 if trust2 != 10
{txt}(255 missing values generated)

{com}. gen trust_index = (first_trust + second_trust)/2
{txt}(325 missing values generated)

{com}. 
. *creating index for policy attitudes*
. gen dril_attitude = (attitude_drilling - 1)/6*(-1)+1 if attitude_drilling != 8
{txt}(197 missing values generated)

{com}. gen air_attitude = (attitude_air - 1)/6*(-1)+1 if attitude_air != 8
{txt}(1,426 missing values generated)

{com}. gen att_index = (dril_attitude + air_attitude)/2
{txt}(1,520 missing values generated)

{com}. 
. *creating index for affective polarization*
. gen dematword = ((word_rating_democrats1) + (word_rating_democrats2*(-1)+6) + word_rating_democrats3 - 3)/4/3 if (word_rating_democrats1 != 6 & word_rating_democrats2 != 6 & word_rating_democrats3 != 6)
{txt}(734 missing values generated)

{com}. gen repatword = ((word_rating_republicans1) + (word_rating_republicans2*(-1)+6) + word_rating_republicans3 - 3)/4/3 if (word_rating_republicans1 != 6 & word_rating_republicans2 != 6 & word_rating_republicans3 != 6)
{txt}(705 missing values generated)

{com}. gen afpolword = repat - demat if Dem0 == 1
{txt}(3,262 missing values generated)

{com}. replace afpolword = demat - repat if Dem0 == 0
{txt}(1,835 real changes made)

{com}. gen afpoltherm = (thermometer_rep - thermometer_dem)/100 if Dem0 == 1
{txt}(3,032 missing values generated)

{com}. replace afpoltherm = (thermometer_dem - thermometer_rep)/100 if Dem0 == 0
{txt}(2,182 real changes made)

{com}. gen afpol_index = (afpoltherm + afpolword)/2
{txt}(1,427 missing values generated)

{com}. gen outpartyaffect = thermometer_dem/100/2 + dematword/2 if Dem0 == 1
{txt}(3,246 missing values generated)

{com}. replace outpartyaffect = thermometer_rep/100/2 + repatword/2 if Dem0 == 0
{txt}(1,900 real changes made)

{com}. gen inpartyaffect = thermometer_rep/100/2 + repatword/2 if Dem0 == 1
{txt}(3,220 missing values generated)

{com}. replace inpartyaffect = thermometer_dem/100/2 + dematword/2 if Dem0 == 0
{txt}(1,894 real changes made)

{com}. 
. *creating variables for manipulation checks*
. gen meanissuepol = ((perceived_issue_pol_drilling + perceived_issue_pol_air)/2-1)/3 if perceived_issue_pol_drilling != 5 & perceived_issue_pol_air != 5
{txt}(2,234 missing values generated)

{com}. replace meanissuepol = (perceived_issue_pol_drilling-1)/6 if perceived_issue_pol_drilling != 8 & sample == 3
{txt}(1,203 real changes made)

{com}. gen meaninc = ((perceived_incivility_drilling + perceived_incivility_air)/2-1)/6*(-1)+1 if perceived_incivility_drilling != 8 & perceived_incivility_air != 8
{txt}(2,190 missing values generated)

{com}. replace meaninc = (perceived_incivility_drilling-1)/6*(-1)+1 if perceived_incivility_drilling != 8 & sample == 3
{txt}(1,183 real changes made)

{com}. 
. *labeling variables*
. 
. label variable low_or_high "High polarization (vs. low)"
{txt}
{com}. label variable civility "Incivility (vs. civility)"
{txt}
{com}. label variable Dem0Rep1 "Republican (vs. Democrat)"
{txt}
{com}. label variable att_index "Policy attitudes (both issues)"
{txt}
{com}. label variable afpol_index "Affective polarization (both issues)"
{txt}
{com}. label variable trust_index "Trust (both issues)"
{txt}
{com}. label variable inpartyaffect "Affect rating of in-party"
{txt}
{com}. label variable outpartyaffect "Affect rating of out-party"
{txt}
{com}. replace treatment_group = 5 if treatment_group == 0
{txt}(642 real changes made)

{com}. label define treatment_group 1 "Low_pol_and_civ" 2 "Low_pol_and_inc" 3 "High_pol_and_civ" 4 "High_pol_and_inc" 5 "Control"
{txt}
{com}. label values treatment_group treatment_group
{txt}
{com}. 
. *************************************************
. **Making results and figure analysis in article**
. *************************************************
. 
. ***Scale reliabilities***
. 
. **Reliabilities reported in section called "Outcome measures"**
. alpha first_trust second_trust if sample == 1 & passed == 1, std item

{txt}Test scale = mean(standardized items)

Average interitem correlation:{col 34}{res}   0.7603
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.8638
{txt}
{com}. alpha afpoltherm afpolword if sample == 1 & passed == 1, std item

{txt}Test scale = mean(standardized items)

Average interitem correlation:{col 34}{res}   0.6811
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.8103
{txt}
{com}. 
. **Reliabilities reported in section called "Follow-up study 1: Using stronger incivility"**
. alpha first_trust second_trust if sample == 2 & passed == 1, std item

{txt}Test scale = mean(standardized items)

Average interitem correlation:{col 34}{res}   0.7636
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.8660
{txt}
{com}. alpha afpoltherm afpolword if sample == 2 & passed == 1, std item

{txt}Test scale = mean(standardized items)

Average interitem correlation:{col 34}{res}   0.6330
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.7753
{txt}
{com}. 
. **Reliabilities reported in section called "Follow-up study 1: Removing metacommentary"**
. alpha afpoltherm afpolword if sample == 1 & passed == 1, item

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .0885134
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.8165
{txt}
{com}. alpha afpoltherm afpolword if sample == 2 & passed == 1, item

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .0623137
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.7753
{txt}
{com}. 
. ***Manipulation checks***
. 
. **Making Figure 2**
. mean meaninc if passed == 1 & sample == 1, over(treatment)
{res}
{txt}Mean estimation{col 48}Number of obs{col 64}= {res}       801

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 27}{c |}       Mean{col 39}   Std. Err.{col 51}     [95% Con{col 64}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.meaninc@treatment_group {c |}
{space 9}Low_pol_and_civ  {c |}{col 27}{res}{space 2} .4014757{col 39}{space 2} .0139022{col 50}{space 5} .3741866{col 64}{space 3} .4287648
{txt}{space 9}Low_pol_and_inc  {c |}{col 27}{res}{space 2} .6929612{col 39}{space 2} .0126849{col 50}{space 5} .6680616{col 64}{space 3} .7178607
{txt}{space 8}High_pol_and_civ  {c |}{col 27}{res}{space 2} .4692982{col 39}{space 2}  .017359{col 50}{space 5} .4352237{col 64}{space 3} .5033728
{txt}{space 8}High_pol_and_inc  {c |}{col 27}{res}{space 2} .7081377{col 39}{space 2} .0140809{col 50}{space 5} .6804979{col 64}{space 3} .7357775
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. mean meanissuepol if passed == 1 & sample == 1, over(treatment)
{res}
{txt}Mean estimation{col 53}Number of obs{col 69}= {res}       811

{txt}{hline 31}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 32}{c |}       Mean{col 44}   Std. Err.{col 56}     [95% Con{col 69}f. Interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.meanissuepol@treatment_group {c |}
{space 14}Low_pol_and_civ  {c |}{col 32}{res}{space 2} .7089947{col 44}{space 2}  .013049{col 55}{space 5} .6833809{col 69}{space 3} .7346086
{txt}{space 14}Low_pol_and_inc  {c |}{col 32}{res}{space 2} .7453469{col 44}{space 2} .0140679{col 55}{space 5}  .717733{col 69}{space 3} .7729608
{txt}{space 13}High_pol_and_civ  {c |}{col 32}{res}{space 2} .8523316{col 44}{space 2}  .015716{col 55}{space 5} .8214827{col 69}{space 3} .8831805
{txt}{space 13}High_pol_and_inc  {c |}{col 32}{res}{space 2} .8670977{col 44}{space 2} .0123755{col 55}{space 5} .8428059{col 69}{space 3} .8913895
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R2
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ci(off) yscale(range(0.2 0.8)) xlabel(,angle(45)) ////
> ylabel(0.2 0.4 0.6 0.8) legend(off) yline(0.333 0.5 0.667, lpattern(dash)) yline(0.2 0.4 0.6 0.8, lpattern(dot)) ///
> xlabel(1 "Low issue pol. / Civility" 2 "Low issue pol. / Incivility" 3 "High issue pol. / Civility" 4 "High issue pol. / Incivility") ///
> ylabel(0.2 0.333 "Slightly polite" 0.4 0.5 "Neither rude nor polite" 0.6 0.667 "Slightly rude" 0.8, angle(0))
{res}{txt}(R1: e(off) not found)
{txt}(R1: e(off) not found)
{txt}(R1: could not determine CI1)
{res}{txt}
{com}. 
. coefplot R2, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ci(off) yscale(range(0.6 1)) xlabel(,angle(45)) ////
> ylabel(0.6 0.7 0.8 0.9 1.0) legend(off) yline(0.667 1, lpattern(dash)) yline(0.6 0.7 0.8 0.9, lpattern(dot)) ///
> xlabel(1 "Low issue pol. / Civility" 2 "Low issue pol. / Incivility" 3 "High issue pol. / Civility" 4 "High issue pol. / Incivility") ///
> ylabel(0.6 0.667 "Somewhat disagree" 0.7 0.8 0.9 1 "Strongly disagree", angle(0))
{res}{txt}(R2: e(off) not found)
{txt}(R2: e(off) not found)
{txt}(R2: could not determine CI1)
{res}{txt}
{com}. 
. *Showing that debate was rated as "rude" in first follow-up as noted in section called "Follow-up study 1: Using stronger incivility"*
. mean meaninc if passed == 1 & sample == 2, over(treatment)
{res}
{txt}Mean estimation{col 48}Number of obs{col 64}= {res}     1,053

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 27}{c |}       Mean{col 39}   Std. Err.{col 51}     [95% Con{col 64}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.meaninc@treatment_group {c |}
{space 9}Low_pol_and_civ  {c |}{col 27}{res}{space 2} .2776753{col 39}{space 2} .0121761{col 50}{space 5} .2537831{col 64}{space 3} .3015675
{txt}{space 9}Low_pol_and_inc  {c |}{col 27}{res}{space 2} .7450617{col 39}{space 2}  .012264{col 50}{space 5}  .720997{col 64}{space 3} .7691264
{txt}{space 8}High_pol_and_civ  {c |}{col 27}{res}{space 2} .3171206{col 39}{space 2} .0135454{col 50}{space 5} .2905416{col 64}{space 3} .3436997
{txt}{space 8}High_pol_and_inc  {c |}{col 27}{res}{space 2}  .775817{col 39}{space 2} .0118718{col 50}{space 5} .7525219{col 64}{space 3} .7991121
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. ***Main study***
. 
. **Making Figure 3 and results reported in section called "Results"**
. 
. *duplicating variables - only necessary to make the coefplot figures*
. gen low_or_high2 = low_or_high_issue_pol
{txt}(1,845 missing values generated)

{com}. gen low_or_high3 = low_or_high_issue_pol
{txt}(1,845 missing values generated)

{com}. gen civility2 = civility_or_incivility
{txt}(642 missing values generated)

{com}. gen civility3 = civility_or_incivility
{txt}(642 missing values generated)

{com}. label variable low_or_high_i "High issue polarization (vs. low)"
{txt}
{com}. label variable low_or_high2 "High issue polarization (vs. low)"
{txt}
{com}. label variable civility2 "Incivility (vs. civility)"
{txt}
{com}. label variable low_or_high3 "High issue polarization (vs. low)"
{txt}
{com}. label variable civility3 "Incivility (vs. civility)"
{txt}
{com}. label variable pol_party "High issue polarization (vs. low)"
{txt}
{com}. label variable civ_party "Incivility (vs. civility)"
{txt}
{com}. 
. *results on trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if sample == 1 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       916
{txt}{hline 13}{c +}{hline 34}   F(2, 913)       = {res}     4.51
{txt}       Model {c |} {res} .545815375         2  .272907687   {txt}Prob > F        ={res}    0.0112
{txt}    Residual {c |} {res} 55.2507658       913  .060515625   {txt}R-squared       ={res}    0.0098
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0076
{txt}       Total {c |} {res} 55.7965812       915   .06097987   {txt}Root MSE        =   {res}   .246

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} -.009279{col 36}{space 2} .0162586{col 47}{space 1}   -0.57{col 56}{space 3}0.568{col 64}{space 4}-.0411876{col 77}{space 3} .0226295
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.047811{col 36}{space 2} .0162726{col 47}{space 1}   -2.94{col 56}{space 3}0.003{col 64}{space 4}-.0797469{col 77}{space 3} -.015875
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3863518{col 36}{space 2} .0142072{col 47}{space 1}   27.19{col 56}{space 3}0.000{col 64}{space 4} .3584693{col 77}{space 3} .4142343
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. test low_or_high_issue_pol = civility_or_incivility

{p 0 7}{space 1}{text:( 1)}{space 1} {res}low_or_high_issue_pol - civility_or_incivility = 0{p_end}

{txt}       F(  1,   913) ={res}    2.76
{txt}{col 13}Prob > F ={res}    0.0971
{txt}
{com}. 
. *results on attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if sample == 1 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       734
{txt}{hline 13}{c +}{hline 34}   F(5, 728)       = {res}   171.15
{txt}       Model {c |} {res} 43.1737262         5  8.63474524   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 36.7280656       728   .05045064   {txt}R-squared       ={res}    0.5403
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5372
{txt}       Total {c |} {res} 79.9017918       733  .109006537   {txt}Root MSE        =   {res} .22461

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2}  .408692{col 26}{space 2} .0286705{col 37}{space 1}   14.25{col 46}{space 3}0.000{col 54}{space 4} .3524053{col 67}{space 3} .4649786
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}  .000541{col 26}{space 2} .0222264{col 37}{space 1}    0.02{col 46}{space 3}0.981{col 54}{space 4}-.0430944{col 67}{space 3} .0441765
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0856764{col 26}{space 2} .0222127{col 37}{space 1}   -3.86{col 46}{space 3}0.000{col 54}{space 4}-.1292851{col 67}{space 3}-.0420678
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .1605411{col 26}{space 2} .0334831{col 37}{space 1}    4.79{col 46}{space 3}0.000{col 54}{space 4} .0948062{col 67}{space 3}  .226276
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0125521{col 26}{space 2} .0334969{col 37}{space 1}   -0.37{col 46}{space 3}0.708{col 54}{space 4}-.0783141{col 67}{space 3} .0532099
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2657821{col 26}{space 2} .0188999{col 37}{space 1}   14.06{col 46}{space 3}0.000{col 54}{space 4} .2286773{col 67}{space 3} .3028868
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *results on affective polarization*
. reg afpol_index low_or_high3 civility3 if sample == 1 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(2, 597)       = {res}     6.78
{txt}       Model {c |} {res} 1.42658452         2   .71329226   {txt}Prob > F        ={res}    0.0012
{txt}    Residual {c |} {res} 62.7644786       597   .10513313   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0189
{txt}       Total {c |} {res} 64.1910632       599  .107163711   {txt}Root MSE        =   {res} .32424

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0689097{col 26}{space 2} .0265394{col 37}{space 1}    2.60{col 46}{space 3}0.010{col 54}{space 4} .0167877{col 67}{space 3} .1210316
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0663968{col 26}{space 2}  .026518{col 37}{space 1}    2.50{col 46}{space 3}0.013{col 54}{space 4}  .014317{col 67}{space 3} .1184766
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3408942{col 26}{space 2} .0233678{col 37}{space 1}   14.59{col 46}{space 3}0.000{col 54}{space 4}  .295001{col 67}{space 3} .3867873
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *Figure 3*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}") legend(off) ///
> coeflabels(, labgap(2)) grid(none) format(%9.1g) mlabel mlabposition(12) xtitle("Change in scale points")
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color and thickness of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(width(medthick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot4.style.editstyle area(linestyle(width(medthick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot7.style.editstyle area(linestyle(width(medthick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color and thickness of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(width(thick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot5.style.editstyle area(linestyle(width(thick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. gr_edit plotregion1.plot8.style.editstyle area(linestyle(width(thick))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing size of value labels*
. gr_edit plotregion1.plot3.style.editstyle label(textstyle(size(medium))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle label(textstyle(size(medium))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle label(textstyle(size(medium))) editcopy
{res}{txt}
{com}. 
. *changing zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. ***Figure 4 and results for follow-up study 1 and 2 and 
. 
. *results on trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if sample == 2 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,042
{txt}{hline 13}{c +}{hline 34}   F(2, 1039)      = {res}    14.50
{txt}       Model {c |} {res} 1.57430778         2   .78715389   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 56.3954156     1,039  .054278552   {txt}R-squared       ={res}    0.0272
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0253
{txt}       Total {c |} {res} 57.9697234     1,041  .055686574   {txt}Root MSE        =   {res} .23298

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0080042{col 36}{space 2} .0144435{col 47}{space 1}    0.55{col 56}{space 3}0.580{col 64}{space 4}-.0203375{col 77}{space 3} .0363459
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0772341{col 36}{space 2} .0144359{col 47}{space 1}   -5.35{col 56}{space 3}0.000{col 64}{space 4}-.1055609{col 77}{space 3}-.0489073
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3847453{col 36}{space 2} .0124002{col 47}{space 1}   31.03{col 56}{space 3}0.000{col 64}{space 4} .3604129{col 77}{space 3} .4090776
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store trust1
{txt}
{com}. reg trust_index civility_or_incivility if sample == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,094
{txt}{hline 13}{c +}{hline 34}   F(1, 1092)      = {res}    23.99
{txt}       Model {c |} {res} 1.28923871         1  1.28923871   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 58.6779006     1,092  .053734341   {txt}R-squared       ={res}    0.0215
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0206
{txt}       Total {c |} {res} 59.9671393     1,093   .05486472   {txt}Root MSE        =   {res} .23181

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
civility_or_incivility {c |}{col 24}{res}{space 2}-.0686604{col 36}{space 2} .0140173{col 47}{space 1}   -4.90{col 56}{space 3}0.000{col 64}{space 4}-.0961643{col 77}{space 3}-.0411564
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  .394219{col 36}{space 2} .0099569{col 47}{space 1}   39.59{col 56}{space 3}0.000{col 64}{space 4}  .374682{col 77}{space 3} .4137559
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store trust2
{txt}
{com}. 
. *results on attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if sample == 2 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       854
{txt}{hline 13}{c +}{hline 34}   F(5, 848)       = {res}   111.51
{txt}       Model {c |} {res} 22.5730107         5  4.51460215   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 34.3313272       848  .040485056   {txt}R-squared       ={res}    0.3967
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3931
{txt}       Total {c |} {res}  56.904338       853   .06671083   {txt}Root MSE        =   {res} .20121

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3179325{col 26}{space 2} .0244027{col 37}{space 1}   13.03{col 46}{space 3}0.000{col 54}{space 4} .2700357{col 67}{space 3} .3658292
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} -.003036{col 26}{space 2} .0173073{col 37}{space 1}   -0.18{col 46}{space 3}0.861{col 54}{space 4}-.0370062{col 67}{space 3} .0309342
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0210558{col 26}{space 2} .0173385{col 37}{space 1}   -1.21{col 46}{space 3}0.225{col 54}{space 4}-.0550872{col 67}{space 3} .0129757
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0622478{col 26}{space 2} .0286539{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .0060069{col 67}{space 3} .1184887
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} -.024345{col 26}{space 2} .0286294{col 37}{space 1}   -0.85{col 46}{space 3}0.395{col 54}{space 4}-.0805379{col 67}{space 3} .0318478
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2669485{col 26}{space 2} .0150037{col 37}{space 1}   17.79{col 46}{space 3}0.000{col 54}{space 4} .2374997{col 67}{space 3} .2963973
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store atpol1
{txt}
{com}. reg dril_attitude Dem0Rep1 civility2 civ_party if sample == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       925
{txt}{hline 13}{c +}{hline 34}   F(3, 921)       = {res}   206.26
{txt}       Model {c |} {res} 40.1104039         3  13.3701346   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 59.7017272       921  .064822722   {txt}R-squared       ={res}    0.4019
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3999
{txt}       Total {c |} {res} 99.8121311       924  .108021787   {txt}Root MSE        =   {res}  .2546

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}dril_attit~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .4305219{col 26}{space 2} .0253619{col 37}{space 1}   16.98{col 46}{space 3}0.000{col 54}{space 4}  .380748{col 67}{space 3} .4802957
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} -.006931{col 26}{space 2} .0202871{col 37}{space 1}   -0.34{col 46}{space 3}0.733{col 54}{space 4}-.0467453{col 67}{space 3} .0328833
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} .0331664{col 26}{space 2} .0359745{col 37}{space 1}    0.92{col 46}{space 3}0.357{col 54}{space 4}-.0374351{col 67}{space 3} .1037678
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1842684{col 26}{space 2} .0146266{col 37}{space 1}   12.60{col 46}{space 3}0.000{col 54}{space 4} .1555632{col 67}{space 3} .2129737
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store atpol2
{txt}
{com}. 
. *extra test - comparing the effect of attitude pol. in follow-up 2 on partisan attitude extremity*
. gen part_att_extremity = dril_attitude if Dem0Rep1 == 1
{txt}(3,084 missing values generated)

{com}. replace part_att_extremity = (-1)*dril_attitude+1 if Dem0Rep1 == 0
{txt}(2,113 real changes made)

{com}. reg part_att_extremity civility2 if sample == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       925
{txt}{hline 13}{c +}{hline 34}   F(1, 923)       = {res}     1.10
{txt}       Model {c |} {res} .080124593         1  .080124593   {txt}Prob > F        ={res}    0.2939
{txt}    Residual {c |} {res} 67.0563312       923  .072650413   {txt}R-squared       ={res}    0.0012
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0001
{txt}       Total {c |} {res} 67.1364558       924  .072658502   {txt}Root MSE        =   {res} .26954

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}part_att_e~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility2 {c |}{col 14}{res}{space 2} .0186172{col 26}{space 2} .0177277{col 37}{space 1}    1.05{col 46}{space 3}0.294{col 54}{space 4} -.016174{col 67}{space 3} .0534085
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7488987{col 26}{space 2}   .01265{col 37}{space 1}   59.20{col 46}{space 3}0.000{col 54}{space 4} .7240725{col 67}{space 3} .7737248
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *results on affective polarization*
. reg afpol_index low_or_high3 civility3 if sample == 2 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       786
{txt}{hline 13}{c +}{hline 34}   F(2, 783)       = {res}     5.98
{txt}       Model {c |} {res}  .94528602         2   .47264301   {txt}Prob > F        ={res}    0.0026
{txt}    Residual {c |} {res} 61.8731527       783  .079020629   {txt}R-squared       ={res}    0.0150
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0125
{txt}       Total {c |} {res} 62.8184387       785  .080023489   {txt}Root MSE        =   {res} .28111

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0437846{col 26}{space 2} .0200646{col 37}{space 1}    2.18{col 46}{space 3}0.029{col 54}{space 4} .0043979{col 67}{space 3} .0831714
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0544069{col 26}{space 2} .0200594{col 37}{space 1}    2.71{col 46}{space 3}0.007{col 54}{space 4} .0150304{col 67}{space 3} .0937835
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2361956{col 26}{space 2} .0171529{col 37}{space 1}   13.77{col 46}{space 3}0.000{col 54}{space 4} .2025244{col 67}{space 3} .2698667
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store afpol1
{txt}
{com}. reg afpol_index civility3 if sample == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       844
{txt}{hline 13}{c +}{hline 34}   F(1, 842)       = {res}    19.16
{txt}       Model {c |} {res} 1.70085988         1  1.70085988   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 74.7488584       842  .088775366   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0211
{txt}       Total {c |} {res} 76.4497183       843  .090687685   {txt}Root MSE        =   {res} .29795

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2} .0897828{col 26}{space 2} .0205119{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 54}{space 4} .0495224{col 67}{space 3} .1300432
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3131359{col 26}{space 2} .0145041{col 37}{space 1}   21.59{col 46}{space 3}0.000{col 54}{space 4} .2846675{col 67}{space 3} .3416042
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store afpol2
{txt}
{com}. 
. *Figure 4*
. coefplot (trust1 atpol1 afpol1), bylabel(First follow-up study) || (trust2 atpol2 afpol2), bylabel(Second follow-up study) byopts(xrescale) drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}") legend(off) ///
> coeflabels(, notick labgap(2)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color and thickness of 90 percent intervals*
. gr_edit plotregion1.plotregion1[2].plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[2].plot1.style.editstyle area(linestyle(width(medthick))) editcopy
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plotregion1[1].plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[1].plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. 
. *changing color and thickness of 95 percent intervals*
. gr_edit plotregion1.plotregion1[1].plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[1].plot2.style.editstyle area(linestyle(width(thick))) editcopy
{res}{txt}
{com}. 
. *changing size of value labels*
. gr_edit plotregion1.plotregion1[2].plot3.style.editstyle label(textstyle(size(medsmall))) editcopy
{res}{txt}
{com}. 
. *changing zero line*
. gr_edit plotregion1.plotregion1[1]._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[1]._xylines[1].style.editstyle linestyle(pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[2]._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plotregion1[2]._xylines[1].style.editstyle linestyle(pattern(dash)) editcopy
{res}{txt}
{com}. 
. *changing headings*
. gr_edit plotregion1.subtitle[1].style.editstyle fillcolor(none) editcopy
{res}{txt}
{com}. gr_edit plotregion1.subtitle[1].style.editstyle linestyle(color(none)) editcopy
{res}{txt}
{com}. 
. *making labels for x-axis*
. gr_edit plotregion1.xaxis1[1].edit_tick 6 0 `"Change in scale points"', custom tickset(major) editstyle(tickstyle(textgap(5)) )
{res}{txt}
{com}. gr_edit plotregion1.xaxis1[2].add_ticks 0 `"Change in scale points"', custom tickset(major) editstyle(tickstyle(textgap(5)) )
{res}{txt}
{com}. 
. ***Making Figur 5 (comparison with benchmark condition)***
. 
. gen T1 = trust_index
{txt}(325 missing values generated)

{com}. gen T2 = trust_index
{txt}(325 missing values generated)

{com}. gen T3 = trust_index
{txt}(325 missing values generated)

{com}. gen T4 = trust_index
{txt}(325 missing values generated)

{com}. gen T5 = trust_index
{txt}(325 missing values generated)

{com}. mean T1 if passed == 1 & treatment == 1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       490

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}T1 {c |}{col 14}{res}{space 2} .3866072{col 26}{space 2} .0110433{col 37}{space 5} .3649089{col 51}{space 3} .4083054
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store T1
{txt}
{com}. mean T2 if passed == 1 & treatment == 2
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       505

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}T2 {c |}{col 14}{res}{space 2} .3207921{col 26}{space 2} .0101989{col 37}{space 5} .3007546{col 51}{space 3} .3408296
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store T2
{txt}
{com}. mean T3 if passed == 1 & treatment == 3
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       472

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}T3 {c |}{col 14}{res}{space 2} .3844015{col 26}{space 2} .0115015{col 37}{space 5} .3618009{col 51}{space 3} .4070021
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store T3
{txt}
{com}. mean T4 if passed == 1 & treatment == 4
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       491

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}T4 {c |}{col 14}{res}{space 2} .3234471{col 26}{space 2} .0105369{col 37}{space 5} .3027439{col 51}{space 3} .3441502
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store T4
{txt}
{com}. mean T5 if passed == 1 & treatment == 5
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       473

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}T5 {c |}{col 14}{res}{space 2} .3020613{col 26}{space 2} .0113627{col 37}{space 5} .2797336{col 51}{space 3}  .324389
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store T5
{txt}
{com}. 
. gen De1 = Dem0
{txt}(850 missing values generated)

{com}. gen De2 = Dem0
{txt}(850 missing values generated)

{com}. gen De3 = Dem0
{txt}(850 missing values generated)

{com}. gen De4 = Dem0
{txt}(850 missing values generated)

{com}. gen De5 = Dem0
{txt}(850 missing values generated)

{com}. regress att_index De1 if treatment == 1 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       409
{txt}{hline 13}{c +}{hline 34}   F(1, 407)       = {res}   292.64
{txt}       Model {c |} {res} 12.5357569         1  12.5357569   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 17.4347668       407  .042837265   {txt}R-squared       ={res}    0.4183
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4168
{txt}       Total {c |} {res} 29.9705237       408  .073457166   {txt}Root MSE        =   {res} .20697

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De1 {c |}{col 14}{res}{space 2} .3565166{col 26}{space 2} .0208408{col 37}{space 1}   17.11{col 46}{space 3}0.000{col 54}{space 4} .3155475{col 67}{space 3} .3974857
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2740055{col 26}{space 2} .0132772{col 37}{space 1}   20.64{col 46}{space 3}0.000{col 54}{space 4}  .247905{col 67}{space 3}  .300106
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R1
{txt}
{com}. regress att_index De2 if treatment == 2 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       412
{txt}{hline 13}{c +}{hline 34}   F(1, 410)       = {res}   247.83
{txt}       Model {c |} {res} 11.6156238         1  11.6156238   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 19.2167647       410  .046870158   {txt}R-squared       ={res}    0.3767
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3752
{txt}       Total {c |} {res} 30.8323885       411  .075017977   {txt}Root MSE        =   {res}  .2165

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De2 {c |}{col 14}{res}{space 2} .3494611{col 26}{space 2} .0221986{col 37}{space 1}   15.74{col 46}{space 3}0.000{col 54}{space 4} .3058238{col 67}{space 3} .3930984
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2579214{col 26}{space 2} .0133497{col 37}{space 1}   19.32{col 46}{space 3}0.000{col 54}{space 4} .2316791{col 67}{space 3} .2841638
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R2
{txt}
{com}. regress att_index De3 if treatment == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       374
{txt}{hline 13}{c +}{hline 34}   F(1, 372)       = {res}   432.88
{txt}       Model {c |} {res} 21.0306404         1  21.0306404   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.0730613       372  .048583498   {txt}R-squared       ={res}    0.5378
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5366
{txt}       Total {c |} {res} 39.1037018       373  .104835662   {txt}Root MSE        =   {res} .22042

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De3 {c |}{col 14}{res}{space 2} .4796719{col 26}{space 2} .0230549{col 37}{space 1}   20.81{col 46}{space 3}0.000{col 54}{space 4} .4343377{col 67}{space 3} .5250061
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2116279{col 26}{space 2} .0150323{col 37}{space 1}   14.08{col 46}{space 3}0.000{col 54}{space 4}  .182069{col 67}{space 3} .2411868
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R3
{txt}
{com}. regress att_index De4 if treatment == 4 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       393
{txt}{hline 13}{c +}{hline 34}   F(1, 391)       = {res}   396.43
{txt}       Model {c |} {res} 19.1174755         1  19.1174755   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.8557352       391  .048224387   {txt}R-squared       ={res}    0.5034
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5022
{txt}       Total {c |} {res} 37.9732107       392  .096870435   {txt}Root MSE        =   {res}  .2196

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De4 {c |}{col 14}{res}{space 2} .4489248{col 26}{space 2} .0225472{col 37}{space 1}   19.91{col 46}{space 3}0.000{col 54}{space 4}  .404596{col 67}{space 3} .4932536
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2213877{col 26}{space 2} .0143865{col 37}{space 1}   15.39{col 46}{space 3}0.000{col 54}{space 4} .1931031{col 67}{space 3} .2496723
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R4
{txt}
{com}. regress att_index De5 if treatment == 5 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       376
{txt}{hline 13}{c +}{hline 34}   F(1, 374)       = {res}   211.42
{txt}       Model {c |} {res} 10.7811232         1  10.7811232   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 19.0715468       374  .050993441   {txt}R-squared       ={res}    0.3611
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3594
{txt}       Total {c |} {res}   29.85267       375   .07960712   {txt}Root MSE        =   {res} .22582

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De5 {c |}{col 14}{res}{space 2} .3502724{col 26}{space 2} .0240897{col 37}{space 1}   14.54{col 46}{space 3}0.000{col 54}{space 4} .3029042{col 67}{space 3} .3976406
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2634181{col 26}{space 2} .0146995{col 37}{space 1}   17.92{col 46}{space 3}0.000{col 54}{space 4} .2345141{col 67}{space 3}  .292322
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R5
{txt}
{com}. 
. gen A1 = afpol_index
{txt}(1,427 missing values generated)

{com}. gen A2 = afpol_index
{txt}(1,427 missing values generated)

{com}. gen A3 = afpol_index
{txt}(1,427 missing values generated)

{com}. gen A4 = afpol_index
{txt}(1,427 missing values generated)

{com}. gen A5 = afpol_index
{txt}(1,427 missing values generated)

{com}. mean A1 if passed == 1 & treatment == 1
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       346

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}A1 {c |}{col 14}{res}{space 2} .2747592{col 26}{space 2} .0149347{col 37}{space 5} .2453847{col 51}{space 3} .3041336
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store A1
{txt}
{com}. mean A2 if passed == 1 & treatment == 2
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       342

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}A2 {c |}{col 14}{res}{space 2} .3431676{col 26}{space 2}  .016644{col 37}{space 5} .3104298{col 51}{space 3} .3759055
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store A2
{txt}
{com}. mean A3 if passed == 1 & treatment == 3
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       343

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}A3 {c |}{col 14}{res}{space 2} .3396842{col 26}{space 2} .0167716{col 37}{space 5} .3066957{col 51}{space 3} .3726726
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store A3
{txt}
{com}. mean A4 if passed == 1 & treatment == 4
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       355

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}A4 {c |}{col 14}{res}{space 2} .3984038{col 26}{space 2} .0173772{col 37}{space 5} .3642281{col 51}{space 3} .4325794
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store A4
{txt}
{com}. mean A5 if passed == 1 & treatment == 5
{res}
{txt}Mean estimation{col 35}Number of obs{col 51}= {res}       329

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 10}A5 {c |}{col 14}{res}{space 2} .3964995{col 26}{space 2} .0171658{col 37}{space 5} .3627306{col 51}{space 3} .4302684
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store A5
{txt}
{com}. 
. coefplot T1 T2 T3 T4 T5 R1 R2 R3 R4 R5 A1 A2 A3 A4 A5, drop(_cons) vertical scheme(s1mono) fcolor(white) levels(95 90) yscale(range(0 0.50)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4 0.5) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(1) mlabcolor(black)) format(%9.2f) offset(0.0) lcolor(black) ////
> xlabel(1 "Low pol. and civ." 2 "Low pol. and inc." 3 "High pol. and civ." 4 "High pol. and inc." 5 "Benchmark" ////
> 6 "Low pol. and civ." 7 "Low pol. and inc." 8 "High pol. and civ." 9 "High pol. and inc." 10 "Benchmark" ////
> 11 "Low pol. and civ." 12 "Low pol. and inc." 13 "High pol. and civ." 14 "High pol. and inc." 15 "Benchmark", labsize(small)) ////
> xline(5.5 10.5) msymbol(O) mcolor(black) ciopt(color(black)) text(0.56 3 "Trust" 0.56 8 "Attitude polarization" 0.56 13 "Affective polarization")
{res}{txt}
{com}. 
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot11.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot14.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot17.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot20.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot23.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot26.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot29.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot32.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot35.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot38.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot41.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot44.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit .style.editstyle margin(medlarge) editcopy
{res}{txt}
{com}. 
. *********************************************
. **Making results and figures for appendices**
. *********************************************
. 
. ***Appendix A5***
. 
. **Pooled results (excl. resp. who failed attention check)**
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,958
{txt}{hline 13}{c +}{hline 34}   F(2, 1955)      = {res}    17.21
{txt}       Model {c |} {res} 1.96850868         2   .98425434   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 111.819399     1,955  .057196623   {txt}R-squared       ={res}    0.0173
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0163
{txt}       Total {c |} {res} 113.787907     1,957  .058144051   {txt}Root MSE        =   {res} .23916

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}  .000267{col 36}{space 2} .0108111{col 47}{space 1}    0.02{col 56}{space 3}0.980{col 64}{space 4}-.0209354{col 77}{space 3} .0214694
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0634247{col 36}{space 2} .0108112{col 47}{space 1}   -5.87{col 56}{space 3}0.000{col 64}{space 4}-.0846274{col 77}{space 3}-.0422219
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3853939{col 36}{space 2} .0093591{col 47}{space 1}   41.18{col 56}{space 3}0.000{col 64}{space 4} .3670391{col 77}{space 3} .4037488
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,588
{txt}{hline 13}{c +}{hline 34}   F(5, 1582)      = {res}   277.44
{txt}       Model {c |} {res} 64.5546024         5  12.9109205   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 73.6201249     1,582  .046536109   {txt}R-squared       ={res}    0.4672
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4655
{txt}       Total {c |} {res} 138.174727     1,587  .087066621   {txt}Root MSE        =   {res} .21572

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3623115{col 26}{space 2} .0189284{col 37}{space 1}   19.14{col 46}{space 3}0.000{col 54}{space 4}  .325184{col 67}{space 3} .3994389
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0039481{col 26}{space 2} .0139796{col 37}{space 1}   -0.28{col 46}{space 3}0.778{col 54}{space 4}-.0313686{col 67}{space 3} .0234725
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0489404{col 26}{space 2} .0139944{col 37}{space 1}   -3.50{col 46}{space 3}0.000{col 54}{space 4}  -.07639{col 67}{space 3}-.0214909
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .1107667{col 26}{space 2} .0221291{col 37}{space 1}    5.01{col 46}{space 3}0.000{col 54}{space 4} .0673612{col 67}{space 3} .1541722
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} -.018107{col 26}{space 2} .0221237{col 37}{space 1}   -0.82{col 46}{space 3}0.413{col 54}{space 4}-.0615019{col 67}{space 3}  .025288
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2676977{col 26}{space 2} .0120318{col 37}{space 1}   22.25{col 46}{space 3}0.000{col 54}{space 4} .2440977{col 67}{space 3} .2912976
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,386
{txt}{hline 13}{c +}{hline 34}   F(2, 1383)      = {res}    14.26
{txt}       Model {c |} {res} 2.67840377         2  1.33920189   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  129.88491     1,383  .093915337   {txt}R-squared       ={res}    0.0202
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0188
{txt}       Total {c |} {res} 132.563314     1,385  .095713584   {txt}Root MSE        =   {res} .30646

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0600534{col 26}{space 2} .0164648{col 37}{space 1}    3.65{col 46}{space 3}0.000{col 54}{space 4} .0277547{col 67}{space 3} .0923521
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0635297{col 26}{space 2} .0164647{col 37}{space 1}    3.86{col 46}{space 3}0.000{col 54}{space 4} .0312313{col 67}{space 3} .0958281
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2771844{col 26}{space 2}  .014265{col 37}{space 1}   19.43{col 46}{space 3}0.000{col 54}{space 4}  .249201{col 67}{space 3} .3051677
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **Main study (excl. resp. who failed attention check)**
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       916
{txt}{hline 13}{c +}{hline 34}   F(2, 913)       = {res}     4.51
{txt}       Model {c |} {res} .545815375         2  .272907687   {txt}Prob > F        ={res}    0.0112
{txt}    Residual {c |} {res} 55.2507658       913  .060515625   {txt}R-squared       ={res}    0.0098
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0076
{txt}       Total {c |} {res} 55.7965812       915   .06097987   {txt}Root MSE        =   {res}   .246

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} -.009279{col 36}{space 2} .0162586{col 47}{space 1}   -0.57{col 56}{space 3}0.568{col 64}{space 4}-.0411876{col 77}{space 3} .0226295
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.047811{col 36}{space 2} .0162726{col 47}{space 1}   -2.94{col 56}{space 3}0.003{col 64}{space 4}-.0797469{col 77}{space 3} -.015875
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3863518{col 36}{space 2} .0142072{col 47}{space 1}   27.19{col 56}{space 3}0.000{col 64}{space 4} .3584693{col 77}{space 3} .4142343
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1 & sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       734
{txt}{hline 13}{c +}{hline 34}   F(5, 728)       = {res}   171.15
{txt}       Model {c |} {res} 43.1737262         5  8.63474524   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 36.7280656       728   .05045064   {txt}R-squared       ={res}    0.5403
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5372
{txt}       Total {c |} {res} 79.9017918       733  .109006537   {txt}Root MSE        =   {res} .22461

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2}  .408692{col 26}{space 2} .0286705{col 37}{space 1}   14.25{col 46}{space 3}0.000{col 54}{space 4} .3524053{col 67}{space 3} .4649786
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}  .000541{col 26}{space 2} .0222264{col 37}{space 1}    0.02{col 46}{space 3}0.981{col 54}{space 4}-.0430944{col 67}{space 3} .0441765
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0856764{col 26}{space 2} .0222127{col 37}{space 1}   -3.86{col 46}{space 3}0.000{col 54}{space 4}-.1292851{col 67}{space 3}-.0420678
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .1605411{col 26}{space 2} .0334831{col 37}{space 1}    4.79{col 46}{space 3}0.000{col 54}{space 4} .0948062{col 67}{space 3}  .226276
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0125521{col 26}{space 2} .0334969{col 37}{space 1}   -0.37{col 46}{space 3}0.708{col 54}{space 4}-.0783141{col 67}{space 3} .0532099
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2657821{col 26}{space 2} .0188999{col 37}{space 1}   14.06{col 46}{space 3}0.000{col 54}{space 4} .2286773{col 67}{space 3} .3028868
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(2, 597)       = {res}     6.78
{txt}       Model {c |} {res} 1.42658452         2   .71329226   {txt}Prob > F        ={res}    0.0012
{txt}    Residual {c |} {res} 62.7644786       597   .10513313   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0189
{txt}       Total {c |} {res} 64.1910632       599  .107163711   {txt}Root MSE        =   {res} .32424

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0689097{col 26}{space 2} .0265394{col 37}{space 1}    2.60{col 46}{space 3}0.010{col 54}{space 4} .0167877{col 67}{space 3} .1210316
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0663968{col 26}{space 2}  .026518{col 37}{space 1}    2.50{col 46}{space 3}0.013{col 54}{space 4}  .014317{col 67}{space 3} .1184766
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3408942{col 26}{space 2} .0233678{col 37}{space 1}   14.59{col 46}{space 3}0.000{col 54}{space 4}  .295001{col 67}{space 3} .3867873
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **Follow up 1 (excl. resp. who failed attention check)**
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,042
{txt}{hline 13}{c +}{hline 34}   F(2, 1039)      = {res}    14.50
{txt}       Model {c |} {res} 1.57430778         2   .78715389   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 56.3954156     1,039  .054278552   {txt}R-squared       ={res}    0.0272
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0253
{txt}       Total {c |} {res} 57.9697234     1,041  .055686574   {txt}Root MSE        =   {res} .23298

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0080042{col 36}{space 2} .0144435{col 47}{space 1}    0.55{col 56}{space 3}0.580{col 64}{space 4}-.0203375{col 77}{space 3} .0363459
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0772341{col 36}{space 2} .0144359{col 47}{space 1}   -5.35{col 56}{space 3}0.000{col 64}{space 4}-.1055609{col 77}{space 3}-.0489073
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3847453{col 36}{space 2} .0124002{col 47}{space 1}   31.03{col 56}{space 3}0.000{col 64}{space 4} .3604129{col 77}{space 3} .4090776
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       854
{txt}{hline 13}{c +}{hline 34}   F(5, 848)       = {res}   111.51
{txt}       Model {c |} {res} 22.5730107         5  4.51460215   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 34.3313272       848  .040485056   {txt}R-squared       ={res}    0.3967
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3931
{txt}       Total {c |} {res}  56.904338       853   .06671083   {txt}Root MSE        =   {res} .20121

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3179325{col 26}{space 2} .0244027{col 37}{space 1}   13.03{col 46}{space 3}0.000{col 54}{space 4} .2700357{col 67}{space 3} .3658292
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} -.003036{col 26}{space 2} .0173073{col 37}{space 1}   -0.18{col 46}{space 3}0.861{col 54}{space 4}-.0370062{col 67}{space 3} .0309342
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0210558{col 26}{space 2} .0173385{col 37}{space 1}   -1.21{col 46}{space 3}0.225{col 54}{space 4}-.0550872{col 67}{space 3} .0129757
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0622478{col 26}{space 2} .0286539{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .0060069{col 67}{space 3} .1184887
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} -.024345{col 26}{space 2} .0286294{col 37}{space 1}   -0.85{col 46}{space 3}0.395{col 54}{space 4}-.0805379{col 67}{space 3} .0318478
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2669485{col 26}{space 2} .0150037{col 37}{space 1}   17.79{col 46}{space 3}0.000{col 54}{space 4} .2374997{col 67}{space 3} .2963973
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       786
{txt}{hline 13}{c +}{hline 34}   F(2, 783)       = {res}     5.98
{txt}       Model {c |} {res}  .94528602         2   .47264301   {txt}Prob > F        ={res}    0.0026
{txt}    Residual {c |} {res} 61.8731527       783  .079020629   {txt}R-squared       ={res}    0.0150
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0125
{txt}       Total {c |} {res} 62.8184387       785  .080023489   {txt}Root MSE        =   {res} .28111

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0437846{col 26}{space 2} .0200646{col 37}{space 1}    2.18{col 46}{space 3}0.029{col 54}{space 4} .0043979{col 67}{space 3} .0831714
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0544069{col 26}{space 2} .0200594{col 37}{space 1}    2.71{col 46}{space 3}0.007{col 54}{space 4} .0150304{col 67}{space 3} .0937835
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2361956{col 26}{space 2} .0171529{col 37}{space 1}   13.77{col 46}{space 3}0.000{col 54}{space 4} .2025244{col 67}{space 3} .2698667
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **Follow up 2 (excl. resp. who failed attention check)**
. 
. *trust*
. reg trust_index civility_or_incivility if passed == 1 & sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,094
{txt}{hline 13}{c +}{hline 34}   F(1, 1092)      = {res}    23.99
{txt}       Model {c |} {res} 1.28923871         1  1.28923871   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 58.6779006     1,092  .053734341   {txt}R-squared       ={res}    0.0215
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0206
{txt}       Total {c |} {res} 59.9671393     1,093   .05486472   {txt}Root MSE        =   {res} .23181

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
civility_or_incivility {c |}{col 24}{res}{space 2}-.0686604{col 36}{space 2} .0140173{col 47}{space 1}   -4.90{col 56}{space 3}0.000{col 64}{space 4}-.0961643{col 77}{space 3}-.0411564
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  .394219{col 36}{space 2} .0099569{col 47}{space 1}   39.59{col 56}{space 3}0.000{col 64}{space 4}  .374682{col 77}{space 3} .4137559
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg dril_at Dem0Rep1 civility2 civ_party if passed == 1 & sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       925
{txt}{hline 13}{c +}{hline 34}   F(3, 921)       = {res}   206.26
{txt}       Model {c |} {res} 40.1104039         3  13.3701346   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 59.7017272       921  .064822722   {txt}R-squared       ={res}    0.4019
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3999
{txt}       Total {c |} {res} 99.8121311       924  .108021787   {txt}Root MSE        =   {res}  .2546

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}dril_attit~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .4305219{col 26}{space 2} .0253619{col 37}{space 1}   16.98{col 46}{space 3}0.000{col 54}{space 4}  .380748{col 67}{space 3} .4802957
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} -.006931{col 26}{space 2} .0202871{col 37}{space 1}   -0.34{col 46}{space 3}0.733{col 54}{space 4}-.0467453{col 67}{space 3} .0328833
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} .0331664{col 26}{space 2} .0359745{col 37}{space 1}    0.92{col 46}{space 3}0.357{col 54}{space 4}-.0374351{col 67}{space 3} .1037678
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1842684{col 26}{space 2} .0146266{col 37}{space 1}   12.60{col 46}{space 3}0.000{col 54}{space 4} .1555632{col 67}{space 3} .2129737
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index civility3 if passed == 1 & sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       844
{txt}{hline 13}{c +}{hline 34}   F(1, 842)       = {res}    19.16
{txt}       Model {c |} {res} 1.70085988         1  1.70085988   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 74.7488584       842  .088775366   {txt}R-squared       ={res}    0.0222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0211
{txt}       Total {c |} {res} 76.4497183       843  .090687685   {txt}Root MSE        =   {res} .29795

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2} .0897828{col 26}{space 2} .0205119{col 37}{space 1}    4.38{col 46}{space 3}0.000{col 54}{space 4} .0495224{col 67}{space 3} .1300432
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3131359{col 26}{space 2} .0145041{col 37}{space 1}   21.59{col 46}{space 3}0.000{col 54}{space 4} .2846675{col 67}{space 3} .3416042
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(civility_or_incivility="{c -(}bf:Effects on trust in politicians{c )-}" civ_party="{c -(}bf:Effects on attitude polarization{c )-}" civility3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. ***Appendix A6***
. 
. **Pooled results (incl. resp. who failed attention check)**
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     2,261
{txt}{hline 13}{c +}{hline 34}   F(2, 2258)      = {res}    13.93
{txt}       Model {c |} {res} 1.62446587         2  .812232937   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 131.706896     2,258  .058329006   {txt}R-squared       ={res}    0.0122
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0113
{txt}       Total {c |} {res} 133.331362     2,260  .058996178   {txt}Root MSE        =   {res} .24151

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} -.003625{col 36}{space 2} .0101601{col 47}{space 1}   -0.36{col 56}{space 3}0.721{col 64}{space 4}-.0235491{col 77}{space 3} .0162991
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.053556{col 36}{space 2} .0101628{col 47}{space 1}   -5.27{col 56}{space 3}0.000{col 64}{space 4}-.0734855{col 77}{space 3}-.0336266
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3863921{col 36}{space 2}  .008884{col 47}{space 1}   43.49{col 56}{space 3}0.000{col 64}{space 4} .3689704{col 77}{space 3} .4038138
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,818
{txt}{hline 13}{c +}{hline 34}   F(5, 1812)      = {res}   245.04
{txt}       Model {c |} {res} 63.5533246         5  12.7106649   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 93.9902484     1,812  .051870998   {txt}R-squared       ={res}    0.4034
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4018
{txt}       Total {c |} {res} 157.543573     1,817  .086705324   {txt}Root MSE        =   {res} .22775

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3403814{col 26}{space 2} .0189112{col 37}{space 1}   18.00{col 46}{space 3}0.000{col 54}{space 4} .3032914{col 67}{space 3} .3774714
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} .0018869{col 26}{space 2} .0137751{col 37}{space 1}    0.14{col 46}{space 3}0.891{col 54}{space 4}-.0251299{col 67}{space 3} .0289037
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0484891{col 26}{space 2} .0137997{col 37}{space 1}   -3.51{col 46}{space 3}0.000{col 54}{space 4} -.075554{col 67}{space 3}-.0214241
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0943075{col 26}{space 2} .0218562{col 37}{space 1}    4.31{col 46}{space 3}0.000{col 54}{space 4} .0514414{col 67}{space 3} .1371736
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} -.015412{col 26}{space 2} .0218355{col 37}{space 1}   -0.71{col 46}{space 3}0.480{col 54}{space 4}-.0582375{col 67}{space 3} .0274134
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2901779{col 26}{space 2} .0118713{col 37}{space 1}   24.44{col 46}{space 3}0.000{col 54}{space 4} .2668951{col 67}{space 3} .3134607
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,603
{txt}{hline 13}{c +}{hline 34}   F(2, 1600)      = {res}    11.75
{txt}       Model {c |} {res} 2.24264957         2  1.12132478   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 152.630877     1,600  .095394298   {txt}R-squared       ={res}    0.0145
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0132
{txt}       Total {c |} {res} 154.873527     1,602   .09667511   {txt}Root MSE        =   {res} .30886

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0560363{col 26}{space 2} .0154304{col 37}{space 1}    3.63{col 46}{space 3}0.000{col 54}{space 4} .0257704{col 67}{space 3} .0863022
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}  .050317{col 26}{space 2} .0154324{col 37}{space 1}    3.26{col 46}{space 3}0.001{col 54}{space 4} .0200471{col 67}{space 3} .0805868
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .266455{col 26}{space 2} .0135402{col 37}{space 1}   19.68{col 46}{space 3}0.000{col 54}{space 4} .2398966{col 67}{space 3} .2930133
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *Main study (incl. resp. who failed attention check)*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,088
{txt}{hline 13}{c +}{hline 34}   F(2, 1085)      = {res}     2.82
{txt}       Model {c |} {res} .347453186         2  .173726593   {txt}Prob > F        ={res}    0.0597
{txt}    Residual {c |} {res} 66.7241642     1,085  .061496926   {txt}R-squared       ={res}    0.0052
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0033
{txt}       Total {c |} {res} 67.0716174     1,087   .06170342   {txt}Root MSE        =   {res} .24799

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0159908{col 36}{space 2} .0150394{col 47}{space 1}   -1.06{col 56}{space 3}0.288{col 64}{space 4}-.0455004{col 77}{space 3} .0135188
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0323024{col 36}{space 2} .0150562{col 47}{space 1}   -2.15{col 56}{space 3}0.032{col 64}{space 4} -.061845{col 77}{space 3}-.0027599
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3914564{col 36}{space 2} .0133553{col 47}{space 1}   29.31{col 56}{space 3}0.000{col 64}{space 4} .3652513{col 77}{space 3} .4176615
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       864
{txt}{hline 13}{c +}{hline 34}   F(5, 858)       = {res}   130.99
{txt}       Model {c |} {res} 39.4710962         5  7.89421924   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 51.7071344       858  .060264725   {txt}R-squared       ={res}    0.4329
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4296
{txt}       Total {c |} {res} 91.1782306       863  .105652643   {txt}Root MSE        =   {res} .24549

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3688307{col 26}{space 2} .0295455{col 37}{space 1}   12.48{col 46}{space 3}0.000{col 54}{space 4} .3108408{col 67}{space 3} .4268207
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} .0147271{col 26}{space 2} .0219945{col 37}{space 1}    0.67{col 46}{space 3}0.503{col 54}{space 4}-.0284422{col 67}{space 3} .0578963
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0879448{col 26}{space 2} .0220109{col 37}{space 1}   -4.00{col 46}{space 3}0.000{col 54}{space 4}-.1311463{col 67}{space 3}-.0447433
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2}  .138591{col 26}{space 2} .0339002{col 37}{space 1}    4.09{col 46}{space 3}0.000{col 54}{space 4} .0720539{col 67}{space 3}  .205128
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0203409{col 26}{space 2} .0338564{col 37}{space 1}   -0.60{col 46}{space 3}0.548{col 54}{space 4}-.0867919{col 67}{space 3}   .04611
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .310373{col 26}{space 2} .0188897{col 37}{space 1}   16.43{col 46}{space 3}0.000{col 54}{space 4} .2732977{col 67}{space 3} .3474484
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if sample == 1 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       723
{txt}{hline 13}{c +}{hline 34}   F(2, 720)       = {res}     5.01
{txt}       Model {c |} {res} 1.10101243         2  .550506214   {txt}Prob > F        ={res}    0.0069
{txt}    Residual {c |} {res} 79.1399316       720  .109916572   {txt}R-squared       ={res}    0.0137
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0110
{txt}       Total {c |} {res}  80.240944       722  .111137042   {txt}Root MSE        =   {res} .33154

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0678367{col 26}{space 2}   .02469{col 37}{space 1}    2.75{col 46}{space 3}0.006{col 54}{space 4} .0193636{col 67}{space 3} .1163098
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}  .039444{col 26}{space 2}  .024697{col 37}{space 1}    1.60{col 46}{space 3}0.111{col 54}{space 4}-.0090428{col 67}{space 3} .0879309
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3184256{col 26}{space 2} .0221842{col 37}{space 1}   14.35{col 46}{space 3}0.000{col 54}{space 4} .2748722{col 67}{space 3}  .361979
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *Follow up 1 (incl. resp. who failed attention check)*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,173
{txt}{hline 13}{c +}{hline 34}   F(2, 1170)      = {res}    14.79
{txt}       Model {c |} {res} 1.62901034         2  .814505168   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 64.4472157     1,170   .05508309   {txt}R-squared       ={res}    0.0247
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0230
{txt}       Total {c |} {res} 66.0762261     1,172  .056379032   {txt}Root MSE        =   {res}  .2347

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0073114{col 36}{space 2} .0137123{col 47}{space 1}    0.53{col 56}{space 3}0.594{col 64}{space 4} -.019592{col 77}{space 3} .0342147
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0740945{col 36}{space 2} .0137064{col 47}{space 1}   -5.41{col 56}{space 3}0.000{col 64}{space 4}-.1009864{col 77}{space 3}-.0472026
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3821695{col 36}{space 2} .0118208{col 47}{space 1}   32.33{col 56}{space 3}0.000{col 64}{space 4} .3589771{col 77}{space 3} .4053618
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index Dem0Rep1 civility2 low_or_high2 pol_party civ_party if sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       954
{txt}{hline 13}{c +}{hline 34}   F(5, 948)       = {res}   117.24
{txt}       Model {c |} {res} 24.4740741         5  4.89481483   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 39.5808178       948  .041751918   {txt}R-squared       ={res}    0.3821
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3788
{txt}       Total {c |} {res} 64.0548919       953  .067213947   {txt}Root MSE        =   {res} .20433

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3106539{col 26}{space 2} .0234645{col 37}{space 1}   13.24{col 46}{space 3}0.000{col 54}{space 4} .2646055{col 67}{space 3} .3567023
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0074938{col 26}{space 2} .0167722{col 37}{space 1}   -0.45{col 46}{space 3}0.655{col 54}{space 4}-.0404087{col 67}{space 3}  .025421
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0159313{col 26}{space 2} .0168102{col 37}{space 1}   -0.95{col 46}{space 3}0.344{col 54}{space 4}-.0489208{col 67}{space 3} .0170582
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0500844{col 26}{space 2} .0273569{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4}-.0036027{col 67}{space 3} .1037715
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0114263{col 26}{space 2} .0273335{col 37}{space 1}   -0.42{col 46}{space 3}0.676{col 54}{space 4}-.0650676{col 67}{space 3} .0422149
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2725649{col 26}{space 2} .0144848{col 37}{space 1}   18.82{col 46}{space 3}0.000{col 54}{space 4}  .244139{col 67}{space 3} .3009908
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       880
{txt}{hline 13}{c +}{hline 34}   F(2, 877)       = {res}     6.04
{txt}       Model {c |} {res} .961598935         2  .480799467   {txt}Prob > F        ={res}    0.0025
{txt}    Residual {c |} {res} 69.7651913       877  .079549819   {txt}R-squared       ={res}    0.0136
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0113
{txt}       Total {c |} {res} 70.7267902       879  .080462788   {txt}Root MSE        =   {res} .28205

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0400017{col 26}{space 2} .0190247{col 37}{space 1}    2.10{col 46}{space 3}0.036{col 54}{space 4} .0026624{col 67}{space 3}  .077341
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0533949{col 26}{space 2}   .01902{col 37}{space 1}    2.81{col 46}{space 3}0.005{col 54}{space 4} .0160649{col 67}{space 3}  .090725
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2296771{col 26}{space 2} .0163717{col 37}{space 1}   14.03{col 46}{space 3}0.000{col 54}{space 4} .1975448{col 67}{space 3} .2618093
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *Follow up 2 (incl. resp. who failed attention check)*
. 
. *trust*
. reg trust_index civility_or_incivility if sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,177
{txt}{hline 13}{c +}{hline 34}   F(1, 1175)      = {res}    26.87
{txt}       Model {c |} {res} 1.44393242         1  1.44393242   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 63.1505465     1,175  .053745146   {txt}R-squared       ={res}    0.0224
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0215
{txt}       Total {c |} {res} 64.5944789     1,176  .054927278   {txt}Root MSE        =   {res} .23183

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
civility_or_incivility {c |}{col 24}{res}{space 2}-.0700512{col 36}{space 2} .0135149{col 47}{space 1}   -5.18{col 56}{space 3}0.000{col 64}{space 4}-.0965671{col 77}{space 3}-.0435352
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3932513{col 36}{space 2} .0095524{col 47}{space 1}   41.17{col 56}{space 3}0.000{col 64}{space 4} .3745097{col 77}{space 3} .4119929
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg dril_at Dem0Rep1 civility2 civ_party if sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       990
{txt}{hline 13}{c +}{hline 34}   F(3, 986)       = {res}   221.76
{txt}       Model {c |} {res} 43.2187497         3  14.4062499   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 64.0524333       986    .0649619   {txt}R-squared       ={res}    0.4029
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4011
{txt}       Total {c |} {res} 107.271183       989   .10846429   {txt}Root MSE        =   {res} .25488

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}dril_attit~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .4212075{col 26}{space 2} .0241302{col 37}{space 1}   17.46{col 46}{space 3}0.000{col 54}{space 4}  .373855{col 67}{space 3}   .46856
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0116258{col 26}{space 2} .0197653{col 37}{space 1}   -0.59{col 46}{space 3}0.557{col 54}{space 4}-.0504128{col 67}{space 3} .0271612
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} .0484335{col 26}{space 2}  .034571{col 37}{space 1}    1.40{col 46}{space 3}0.162{col 54}{space 4}-.0194076{col 67}{space 3} .1162746
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1879543{col 26}{space 2} .0142258{col 37}{space 1}   13.21{col 46}{space 3}0.000{col 54}{space 4}  .160038{col 67}{space 3} .2158706
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index civility3 if sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       899
{txt}{hline 13}{c +}{hline 34}   F(1, 897)       = {res}    21.56
{txt}       Model {c |} {res} 1.93147806         1  1.93147806   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 80.3738624       897  .089602968   {txt}R-squared       ={res}    0.0235
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0224
{txt}       Total {c |} {res} 82.3053404       898  .091654054   {txt}Root MSE        =   {res} .29934

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2} .0927079{col 26}{space 2} .0199679{col 37}{space 1}    4.64{col 46}{space 3}0.000{col 54}{space 4} .0535186{col 67}{space 3} .1318972
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3088913{col 26}{space 2} .0140486{col 37}{space 1}   21.99{col 46}{space 3}0.000{col 54}{space 4} .2813194{col 67}{space 3} .3364633
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(civility_or_incivility="{c -(}bf:Effects on trust in politicians{c )-}" civ_party="{c -(}bf:Effects on attitude polarization{c )-}" civility3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) 
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. ***Appendix A7***
. 
. **Note: Results from these analyses are also used in footnote 13**
. 
. *Pooled results*
. 
. reg inpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,437
{txt}{hline 13}{c +}{hline 34}   F(2, 1434)      = {res}    13.73
{txt}       Model {c |} {res} .976570156         2  .488285078   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 51.0125363     1,434  .035573596   {txt}R-squared       ={res}    0.0188
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0174
{txt}       Total {c |} {res} 51.9891064     1,436  .036204113   {txt}Root MSE        =   {res} .18861

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         inpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0146143{col 36}{space 2} .0099515{col 47}{space 1}    1.47{col 56}{space 3}0.142{col 64}{space 4}-.0049068{col 77}{space 3} .0341354
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0502055{col 36}{space 2} .0099526{col 47}{space 1}   -5.04{col 56}{space 3}0.000{col 64}{space 4}-.0697287{col 77}{space 3}-.0306823
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .7192896{col 36}{space 2} .0086363{col 47}{space 1}   83.29{col 56}{space 3}0.000{col 64}{space 4} .7023485{col 77}{space 3} .7362307
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store In_party_affect
{txt}
{com}. reg outpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,419
{txt}{hline 13}{c +}{hline 34}   F(2, 1416)      = {res}    58.22
{txt}       Model {c |} {res} 5.44389427         2  2.72194714   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 66.2045978     1,416  .046754659   {txt}R-squared       ={res}    0.0760
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0747
{txt}       Total {c |} {res} 71.6484921     1,418  .050527851   {txt}Root MSE        =   {res} .21623

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        outpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0462734{col 36}{space 2} .0114808{col 47}{space 1}   -4.03{col 56}{space 3}0.000{col 64}{space 4}-.0687946{col 77}{space 3}-.0237522
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.1144959{col 36}{space 2} .0114814{col 47}{space 1}   -9.97{col 56}{space 3}0.000{col 64}{space 4}-.1370182{col 77}{space 3}-.0919735
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .4387575{col 36}{space 2} .0099589{col 47}{space 1}   44.06{col 56}{space 3}0.000{col 64}{space 4} .4192217{col 77}{space 3} .4582933
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Out_party_affect
{txt}
{com}. 
. coefplot In_party_affect Out_party_affect, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Main study*
. 
. reg inpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       630
{txt}{hline 13}{c +}{hline 34}   F(2, 627)       = {res}     3.82
{txt}       Model {c |} {res} .272032416         2  .136016208   {txt}Prob > F        ={res}    0.0224
{txt}    Residual {c |} {res} 22.3078445       627  .035578699   {txt}R-squared       ={res}    0.0120
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0089
{txt}       Total {c |} {res}  22.579877       629  .035898056   {txt}Root MSE        =   {res} .18862

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         inpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0252071{col 36}{space 2} .0150607{col 47}{space 1}    1.67{col 56}{space 3}0.095{col 64}{space 4}-.0043684{col 77}{space 3} .0547825
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0342649{col 36}{space 2} .0150567{col 47}{space 1}   -2.28{col 56}{space 3}0.023{col 64}{space 4}-.0638326{col 77}{space 3}-.0046972
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .7307934{col 36}{space 2} .0131816{col 47}{space 1}   55.44{col 56}{space 3}0.000{col 64}{space 4}  .704908{col 77}{space 3} .7566787
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store In_party_affect
{txt}
{com}. reg outpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       619
{txt}{hline 13}{c +}{hline 34}   F(2, 616)       = {res}    20.42
{txt}       Model {c |} {res} 1.94043843         2  .970219214   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 29.2752648       616  .047524781   {txt}R-squared       ={res}    0.0622
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0591
{txt}       Total {c |} {res} 31.2157032       618  .050510847   {txt}Root MSE        =   {res}   .218

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        outpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0441876{col 36}{space 2} .0175584{col 47}{space 1}   -2.52{col 56}{space 3}0.012{col 64}{space 4}-.0786693{col 77}{space 3} -.009706
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.1015856{col 36}{space 2} .0175456{col 47}{space 1}   -5.79{col 56}{space 3}0.000{col 64}{space 4} -.136042{col 77}{space 3}-.0671293
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3846863{col 36}{space 2} .0154819{col 47}{space 1}   24.85{col 56}{space 3}0.000{col 64}{space 4} .3542827{col 77}{space 3}   .41509
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Out_party_affect
{txt}
{com}. 
. coefplot In_party_affect Out_party_affect, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 1*
. 
. reg inpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       807
{txt}{hline 13}{c +}{hline 34}   F(2, 804)       = {res}    12.30
{txt}       Model {c |} {res} .852022213         2  .426011107   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 27.8544113       804   .03464479   {txt}R-squared       ={res}    0.0297
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0273
{txt}       Total {c |} {res} 28.7064335       806  .035615923   {txt}Root MSE        =   {res} .18613

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         inpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}  .002523{col 36}{space 2} .0131128{col 47}{space 1}    0.19{col 56}{space 3}0.847{col 64}{space 4}-.0232165{col 77}{space 3} .0282624
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0648902{col 36}{space 2} .0131066{col 47}{space 1}   -4.95{col 56}{space 3}0.000{col 64}{space 4}-.0906174{col 77}{space 3}-.0391629
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .7127047{col 36}{space 2} .0112905{col 47}{space 1}   63.12{col 56}{space 3}0.000{col 64}{space 4} .6905425{col 77}{space 3}  .734867
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store In_party_affect
{txt}
{com}. reg outpartyaffect low_or_high_issue_pol civility_or_incivility if passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       800
{txt}{hline 13}{c +}{hline 34}   F(2, 797)       = {res}    37.65
{txt}       Model {c |} {res} 3.26316803         2  1.63158402   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 34.5386402       797  .043335809   {txt}R-squared       ={res}    0.0863
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0840
{txt}       Total {c |} {res} 37.8018082       799  .047311399   {txt}Root MSE        =   {res} .20817

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        outpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0419404{col 36}{space 2} .0147298{col 47}{space 1}   -2.85{col 56}{space 3}0.005{col 64}{space 4}-.0708543{col 77}{space 3}-.0130265
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.1211016{col 36}{space 2} .0147215{col 47}{space 1}   -8.23{col 56}{space 3}0.000{col 64}{space 4}-.1499992{col 77}{space 3} -.092204
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  .475744{col 36}{space 2} .0126038{col 47}{space 1}   37.75{col 56}{space 3}0.000{col 64}{space 4} .4510034{col 77}{space 3} .5004847
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Out_party_affect
{txt}
{com}. 
. coefplot In_party_affect Out_party_affect, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 2*
. 
. reg inpartyaffect civility_or_incivility if passed == 1 & sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       864
{txt}{hline 13}{c +}{hline 34}   F(1, 862)       = {res}     5.06
{txt}       Model {c |} {res} .185846234         1  .185846234   {txt}Prob > F        ={res}    0.0248
{txt}    Residual {c |} {res} 31.6812298       862  .036753167   {txt}R-squared       ={res}    0.0058
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0047
{txt}       Total {c |} {res}  31.867076       863  .036925928   {txt}Root MSE        =   {res} .19171

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         inpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
civility_or_incivility {c |}{col 24}{res}{space 2}-.0293326{col 36}{space 2} .0130443{col 47}{space 1}   -2.25{col 56}{space 3}0.025{col 64}{space 4}-.0549349{col 77}{space 3}-.0037303
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .7081366{col 36}{space 2} .0092237{col 47}{space 1}   76.77{col 56}{space 3}0.000{col 64}{space 4}  .690033{col 77}{space 3} .7262401
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store In_party_affect
{txt}
{com}. reg outpartyaffect civility_or_incivility if passed == 1 & sample == 3

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       867
{txt}{hline 13}{c +}{hline 34}   F(1, 865)       = {res}    71.79
{txt}       Model {c |} {res}  3.1957393         1   3.1957393   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  38.507695       865  .044517566   {txt}R-squared       ={res}    0.0766
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0756
{txt}       Total {c |} {res} 41.7034343       866  .048156391   {txt}Root MSE        =   {res} .21099

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        outpartyaffect{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
civility_or_incivility {c |}{col 24}{res}{space 2} -.121431{col 36}{space 2} .0143321{col 47}{space 1}   -8.47{col 56}{space 3}0.000{col 64}{space 4}-.1495607{col 77}{space 3}-.0933012
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3944561{col 36}{space 2} .0101868{col 47}{space 1}   38.72{col 56}{space 3}0.000{col 64}{space 4} .3744624{col 77}{space 3} .4144498
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Out_party_affect
{txt}
{com}. 
. coefplot In_party_affect Out_party_affect, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. ***Appendix A8***
. 
. *Pooled results*
. 
. reg afpoltherm low_or_high3 civility3 if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,709
{txt}{hline 13}{c +}{hline 34}   F(2, 1706)      = {res}    17.02
{txt}       Model {c |} {res} 3.85600291         2  1.92800146   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 193.208925     1,706  .113252594   {txt}R-squared       ={res}    0.0196
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0184
{txt}       Total {c |} {res} 197.064928     1,708  .115377593   {txt}Root MSE        =   {res} .33653

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  afpoltherm{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0763642{col 26}{space 2} .0162938{col 37}{space 1}    4.69{col 46}{space 3}0.000{col 54}{space 4} .0444062{col 67}{space 3} .1083222
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0561827{col 26}{space 2} .0162814{col 37}{space 1}    3.45{col 46}{space 3}0.001{col 54}{space 4} .0242492{col 67}{space 3} .0881163
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2733683{col 26}{space 2} .0139108{col 37}{space 1}   19.65{col 46}{space 3}0.000{col 54}{space 4} .2460843{col 67}{space 3} .3006522
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Thermomter_questions
{txt}
{com}. reg afpolword low_or_high3 civility3 if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,386
{txt}{hline 13}{c +}{hline 34}   F(2, 1383)      = {res}    11.94
{txt}       Model {c |} {res} 2.61382415         2  1.30691207   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 151.427167     1,383  .109491805   {txt}R-squared       ={res}    0.0170
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0155
{txt}       Total {c |} {res} 154.040991     1,385  .111220932   {txt}Root MSE        =   {res}  .3309

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   afpolword{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0440121{col 26}{space 2} .0177778{col 37}{space 1}    2.48{col 46}{space 3}0.013{col 54}{space 4} .0091376{col 67}{space 3} .0788866
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0743735{col 26}{space 2} .0177777{col 37}{space 1}    4.18{col 46}{space 3}0.000{col 54}{space 4} .0394994{col 67}{space 3} .1092477
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2562707{col 26}{space 2} .0154026{col 37}{space 1}   16.64{col 46}{space 3}0.000{col 54}{space 4} .2260557{col 67}{space 3} .2864857
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Word_questions
{txt}
{com}. 
. coefplot Thermomter_questions Word_questions, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Main study*
. 
. reg afpoltherm low_or_high3 civility3 if passed == 1 & (sample == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       818
{txt}{hline 13}{c +}{hline 34}   F(2, 815)       = {res}    15.19
{txt}       Model {c |} {res} 3.69421215         2  1.84710608   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 99.0792475       815  .121569629   {txt}R-squared       ={res}    0.0359
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0336
{txt}       Total {c |} {res}  102.77346       817  .125793708   {txt}Root MSE        =   {res} .34867

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  afpoltherm{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .1103765{col 26}{space 2} .0244105{col 37}{space 1}    4.52{col 46}{space 3}0.000{col 54}{space 4} .0624617{col 67}{space 3} .1582913
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}  .073091{col 26}{space 2} .0243963{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .0252041{col 67}{space 3} .1209779
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2885256{col 26}{space 2} .0206685{col 37}{space 1}   13.96{col 46}{space 3}0.000{col 54}{space 4} .2479558{col 67}{space 3} .3290955
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Thermomter_questions
{txt}
{com}. reg afpolword low_or_high3 civility3 if passed == 1 & (sample == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(2, 597)       = {res}     4.19
{txt}       Model {c |} {res} 1.05536397         2  .527681983   {txt}Prob > F        ={res}    0.0156
{txt}    Residual {c |} {res} 75.1529583       597  .125884352   {txt}R-squared       ={res}    0.0138
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0105
{txt}       Total {c |} {res} 76.2083222       599  .127225914   {txt}Root MSE        =   {res}  .3548

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   afpolword{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0333099{col 26}{space 2} .0290407{col 37}{space 1}    1.15{col 46}{space 3}0.252{col 54}{space 4}-.0237244{col 67}{space 3} .0903442
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0757088{col 26}{space 2} .0290173{col 37}{space 1}    2.61{col 46}{space 3}0.009{col 54}{space 4} .0187205{col 67}{space 3} .1326971
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3456716{col 26}{space 2} .0255702{col 37}{space 1}   13.52{col 46}{space 3}0.000{col 54}{space 4} .2954531{col 67}{space 3} .3958901
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Word_questions
{txt}
{com}. 
. coefplot Thermomter_questions Word_questions, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 1*
. 
. reg afpoltherm low_or_high3 civility3 if passed == 1 & (sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       891
{txt}{hline 13}{c +}{hline 34}   F(2, 888)       = {res}     3.63
{txt}       Model {c |} {res} .743059369         2  .371529684   {txt}Prob > F        ={res}    0.0270
{txt}    Residual {c |} {res} 91.0087563       888  .102487338   {txt}R-squared       ={res}    0.0081
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0059
{txt}       Total {c |} {res} 91.7518156       890  .103091928   {txt}Root MSE        =   {res} .32014

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  afpoltherm{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}  .043513{col 26}{space 2} .0214754{col 37}{space 1}    2.03{col 46}{space 3}0.043{col 54}{space 4} .0013646{col 67}{space 3} .0856614
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0389604{col 26}{space 2} .0214549{col 37}{space 1}    1.82{col 46}{space 3}0.070{col 54}{space 4}-.0031478{col 67}{space 3} .0810686
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2609407{col 26}{space 2} .0184659{col 37}{space 1}   14.13{col 46}{space 3}0.000{col 54}{space 4} .2246988{col 67}{space 3} .2971826
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Thermomter_questions
{txt}
{com}. reg afpolword low_or_high3 civility3 if passed == 1 & (sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       786
{txt}{hline 13}{c +}{hline 34}   F(2, 783)       = {res}     6.63
{txt}       Model {c |} {res} 1.16406663         2  .582033315   {txt}Prob > F        ={res}    0.0014
{txt}    Residual {c |} {res} 68.6969032       783  .087735509   {txt}R-squared       ={res}    0.0167
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0142
{txt}       Total {c |} {res} 69.8609699       785  .088994866   {txt}Root MSE        =   {res}  .2962

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   afpolword{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0407553{col 26}{space 2} .0211421{col 37}{space 1}    1.93{col 46}{space 3}0.054{col 54}{space 4}-.0007466{col 67}{space 3} .0822572
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0658635{col 26}{space 2} .0211366{col 37}{space 1}    3.12{col 46}{space 3}0.002{col 54}{space 4} .0243723{col 67}{space 3} .1073546
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1975591{col 26}{space 2} .0180741{col 37}{space 1}   10.93{col 46}{space 3}0.000{col 54}{space 4} .1620798{col 67}{space 3} .2330385
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Word_questions
{txt}
{com}. 
. coefplot Thermomter_questions Word_questions, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 2*
. 
. reg afpoltherm civility3 if passed == 1 & (sample == 3)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       939
{txt}{hline 13}{c +}{hline 34}   F(1, 937)       = {res}    11.28
{txt}       Model {c |} {res} 1.19722043         1  1.19722043   {txt}Prob > F        ={res}    0.0008
{txt}    Residual {c |} {res} 99.4158643       937  .106100175   {txt}R-squared       ={res}    0.0119
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0108
{txt}       Total {c |} {res} 100.613085       938  .107263417   {txt}Root MSE        =   {res} .32573

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  afpoltherm{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2} .0714233{col 26}{space 2} .0212623{col 37}{space 1}    3.36{col 46}{space 3}0.001{col 54}{space 4}  .029696{col 67}{space 3} .1131505
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3480736{col 26}{space 2} .0151543{col 37}{space 1}   22.97{col 46}{space 3}0.000{col 54}{space 4} .3183332{col 67}{space 3}  .377814
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Thermomter_questions
{txt}
{com}. reg afpolword civility3 if passed == 1 & (sample == 3)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       844
{txt}{hline 13}{c +}{hline 34}   F(1, 842)       = {res}    17.84
{txt}       Model {c |} {res} 1.91156525         1  1.91156525   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 90.2074457       842  .107134734   {txt}R-squared       ={res}    0.0208
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0196
{txt}       Total {c |} {res} 92.1190109       843  .109275221   {txt}Root MSE        =   {res} .32731

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   afpolword{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2} .0951817{col 26}{space 2} .0225333{col 37}{space 1}    4.22{col 46}{space 3}0.000{col 54}{space 4} .0509537{col 67}{space 3} .1394096
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .274684{col 26}{space 2} .0159334{col 37}{space 1}   17.24{col 46}{space 3}0.000{col 54}{space 4} .2434102{col 67}{space 3} .3059579
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Word_questions
{txt}
{com}. 
. coefplot Thermomter_questions Word_questions, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. ***Appendix A9***
. 
. *Pooled*
. reg first_trust low_or_high3 civility3 if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,989
{txt}{hline 13}{c +}{hline 34}   F(2, 1986)      = {res}    17.29
{txt}       Model {c |} {res} 2.63147226         2  1.31573613   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 151.135364     1,986  .076100385   {txt}R-squared       ={res}    0.0171
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0161
{txt}       Total {c |} {res} 153.766836     1,988  .077347503   {txt}Root MSE        =   {res} .27586

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} first_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}-.0061511{col 26}{space 2} .0123725{col 37}{space 1}   -0.50{col 46}{space 3}0.619{col 54}{space 4}-.0304155{col 67}{space 3} .0181133
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0724544{col 26}{space 2}  .012373{col 37}{space 1}   -5.86{col 46}{space 3}0.000{col 54}{space 4}-.0967199{col 67}{space 3}-.0481889
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3755416{col 26}{space 2}  .010702{col 37}{space 1}   35.09{col 46}{space 3}0.000{col 54}{space 4} .3545533{col 67}{space 3} .3965299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store First_question
{txt}
{com}. reg second_trust low_or_high3 civility3 if passed == 1 & (sample == 1 | sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,989
{txt}{hline 13}{c +}{hline 34}   F(2, 1986)      = {res}    12.82
{txt}       Model {c |} {res} 1.41110443         2  .705552215   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.294039     1,986  .055032245   {txt}R-squared       ={res}    0.0127
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0118
{txt}       Total {c |} {res} 110.705144     1,988  .055686692   {txt}Root MSE        =   {res} .23459

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}second_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}  .004646{col 26}{space 2} .0105215{col 37}{space 1}    0.44{col 46}{space 3}0.659{col 54}{space 4}-.0159883{col 67}{space 3} .0252803
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0531044{col 26}{space 2} .0105213{col 37}{space 1}   -5.05{col 46}{space 3}0.000{col 54}{space 4}-.0737384{col 67}{space 3}-.0324704
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3957899{col 26}{space 2} .0090885{col 37}{space 1}   43.55{col 46}{space 3}0.000{col 54}{space 4} .3779659{col 67}{space 3}  .413614
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Second_question
{txt}
{com}. 
. coefplot First_question Second_question, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Main study*
. reg first_trust low_or_high3 civility3 if passed == 1 & (sample == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       940
{txt}{hline 13}{c +}{hline 34}   F(2, 937)       = {res}     4.30
{txt}       Model {c |} {res} .685741821         2   .34287091   {txt}Prob > F        ={res}    0.0138
{txt}    Residual {c |} {res} 74.7245453       937  .079748714   {txt}R-squared       ={res}    0.0091
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0070
{txt}       Total {c |} {res} 75.4102872       939  .080309145   {txt}Root MSE        =   {res}  .2824

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} first_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}-.0136269{col 26}{space 2} .0184277{col 37}{space 1}   -0.74{col 46}{space 3}0.460{col 54}{space 4}-.0497913{col 67}{space 3} .0225375
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0519653{col 26}{space 2} .0184411{col 37}{space 1}   -2.82{col 46}{space 3}0.005{col 54}{space 4}-.0881559{col 67}{space 3}-.0157747
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3731819{col 26}{space 2} .0160504{col 37}{space 1}   23.25{col 46}{space 3}0.000{col 54}{space 4}  .341683{col 67}{space 3} .4046808
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store First_question
{txt}
{com}. reg second_trust low_or_high3 civility3 if passed == 1 & (sample == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       942
{txt}{hline 13}{c +}{hline 34}   F(2, 939)       = {res}     3.77
{txt}       Model {c |} {res} .441841164         2  .220920582   {txt}Prob > F        ={res}    0.0235
{txt}    Residual {c |} {res} 55.0891434       939  .058667884   {txt}R-squared       ={res}    0.0080
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0058
{txt}       Total {c |} {res} 55.5309846       941  .059012736   {txt}Root MSE        =   {res} .24221

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}second_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}-.0053691{col 26}{space 2}  .015788{col 37}{space 1}   -0.34{col 46}{space 3}0.734{col 54}{space 4}-.0363529{col 67}{space 3} .0256147
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0428752{col 26}{space 2} .0157948{col 37}{space 1}   -2.71{col 46}{space 3}0.007{col 54}{space 4}-.0738724{col 67}{space 3}-.0118781
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .39924{col 26}{space 2} .0137208{col 37}{space 1}   29.10{col 46}{space 3}0.000{col 54}{space 4}  .372313{col 67}{space 3}  .426167
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Second_question
{txt}
{com}. 
. coefplot First_question Second_question, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 1*
. reg first_trust low_or_high3 civility3 if passed == 1 & (sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,049
{txt}{hline 13}{c +}{hline 34}   F(2, 1046)      = {res}    14.88
{txt}       Model {c |} {res} 2.16629413         2  1.08314707   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 76.1660899     1,046   .07281653   {txt}R-squared       ={res}    0.0277
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0258
{txt}       Total {c |} {res}  78.332384     1,048  .074744641   {txt}Root MSE        =   {res} .26985

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} first_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}-.0003819{col 26}{space 2} .0166714{col 37}{space 1}   -0.02{col 46}{space 3}0.982{col 54}{space 4}-.0330951{col 67}{space 3} .0323312
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0908904{col 26}{space 2} .0166642{col 37}{space 1}   -5.45{col 46}{space 3}0.000{col 54}{space 4}-.1235894{col 67}{space 3}-.0581915
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3778806{col 26}{space 2} .0143283{col 37}{space 1}   26.37{col 46}{space 3}0.000{col 54}{space 4} .3497651{col 67}{space 3} .4059962
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store First_question
{txt}
{com}. reg second_trust low_or_high3 civility3 if passed == 1 & (sample == 2)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,047
{txt}{hline 13}{c +}{hline 34}   F(2, 1044)      = {res}    10.25
{txt}       Model {c |} {res} 1.06214758         2   .53107379   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 54.0924907     1,044  .051812731   {txt}R-squared       ={res}    0.0193
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0174
{txt}       Total {c |} {res} 55.1546383     1,046    .0527291   {txt}Root MSE        =   {res} .22762

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}second_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0131352{col 26}{space 2} .0140769{col 37}{space 1}    0.93{col 46}{space 3}0.351{col 54}{space 4} -.014487{col 67}{space 3} .0407575
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}-.0622207{col 26}{space 2} .0140699{col 37}{space 1}   -4.42{col 46}{space 3}0.000{col 54}{space 4}-.0898292{col 67}{space 3}-.0346121
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3929149{col 26}{space 2} .0120903{col 37}{space 1}   32.50{col 46}{space 3}0.000{col 54}{space 4} .3691907{col 67}{space 3}  .416639
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Second_question
{txt}
{com}. 
. coefplot First_question Second_question, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. *Follow-up study 2*
. reg first_trust civility3 if passed == 1 & (sample == 3)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,101
{txt}{hline 13}{c +}{hline 34}   F(1, 1099)      = {res}    23.25
{txt}       Model {c |} {res} 1.70777996         1  1.70777996   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 80.7265766     1,099  .073454574   {txt}R-squared       ={res}    0.0207
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0198
{txt}       Total {c |} {res} 82.4343566     1,100  .074940324   {txt}Root MSE        =   {res} .27103

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} first_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2}-.0787711{col 26}{space 2} .0163365{col 37}{space 1}   -4.82{col 46}{space 3}0.000{col 54}{space 4}-.1108254{col 67}{space 3}-.0467167
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3760684{col 26}{space 2} .0115988{col 37}{space 1}   32.42{col 46}{space 3}0.000{col 54}{space 4} .3533101{col 67}{space 3} .3988267
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store First_question
{txt}
{com}. reg second_trust civility3 if passed == 1 & (sample == 3)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,097
{txt}{hline 13}{c +}{hline 34}   F(1, 1095)      = {res}    18.26
{txt}       Model {c |} {res} .907520547         1  .907520547   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  54.431871     1,095  .049709471   {txt}R-squared       ={res}    0.0164
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0155
{txt}       Total {c |} {res} 55.3393915     1,096  .050492146   {txt}Root MSE        =   {res} .22296

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}second_trust{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility3 {c |}{col 14}{res}{space 2}-.0575267{col 26}{space 2} .0134636{col 37}{space 1}   -4.27{col 46}{space 3}0.000{col 54}{space 4}-.0839441{col 67}{space 3}-.0311094
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4096967{col 26}{space 2} .0095592{col 37}{space 1}   42.86{col 46}{space 3}0.000{col 54}{space 4} .3909403{col 67}{space 3}  .428453
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Second_question
{txt}
{com}. 
. coefplot First_question Second_question, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) /// legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(col(1))
{res}{txt}
{com}. 
. ***Appendix A11***
. 
. **Intentions-competence**
. 
. *Intentions*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (intentions == 1 & affective == 1 | intentions == 0 & affective == 0)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       950
{txt}{hline 13}{c +}{hline 34}   F(2, 947)       = {res}    10.30
{txt}       Model {c |} {res} 1.12185484         2  .560927419   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 51.5547087       947   .05444003   {txt}R-squared       ={res}    0.0213
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0192
{txt}       Total {c |} {res} 52.6765635       949  .055507443   {txt}Root MSE        =   {res} .23332

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0058777{col 36}{space 2}  .015149{col 47}{space 1}   -0.39{col 56}{space 3}0.698{col 64}{space 4}-.0356073{col 77}{space 3} .0238518
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.068342{col 36}{space 2} .0151447{col 47}{space 1}   -4.51{col 56}{space 3}0.000{col 64}{space 4}-.0980631{col 77}{space 3}-.0386209
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3816436{col 36}{space 2} .0129418{col 47}{space 1}   29.49{col 56}{space 3}0.000{col 64}{space 4} .3562456{col 77}{space 3} .4070415
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. gen att_intentions = .
{txt}(4,335 missing values generated)

{com}. replace att_intentions = dril_attitude if intentions == 1
{txt}(1,760 real changes made)

{com}. replace att_intentions = air_attitude if intentions == 0
{txt}(1,170 real changes made)

{com}. 
. reg att_intentions Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,645
{txt}{hline 13}{c +}{hline 34}   F(5, 1639)      = {res}   166.17
{txt}       Model {c |} {res} 59.5206512         5  11.9041302   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 117.417813     1,639  .071639911   {txt}R-squared       ={res}    0.3364
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3344
{txt}       Total {c |} {res} 176.938465     1,644  .107626803   {txt}Root MSE        =   {res} .26766

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}att_intent~s{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3125797{col 26}{space 2} .0229973{col 37}{space 1}   13.59{col 46}{space 3}0.000{col 54}{space 4} .2674725{col 67}{space 3} .3576869
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0175667{col 26}{space 2} .0170592{col 37}{space 1}   -1.03{col 46}{space 3}0.303{col 54}{space 4}-.0510269{col 67}{space 3} .0158935
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0650879{col 26}{space 2} .0170774{col 37}{space 1}   -3.81{col 46}{space 3}0.000{col 54}{space 4}-.0985838{col 67}{space 3} -.031592
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .1414973{col 26}{space 2} .0269565{col 37}{space 1}    5.25{col 46}{space 3}0.000{col 54}{space 4} .0886244{col 67}{space 3} .1943701
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0014827{col 26}{space 2} .0269565{col 37}{space 1}   -0.06{col 46}{space 3}0.956{col 54}{space 4}-.0543554{col 67}{space 3}   .05139
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2875362{col 26}{space 2}  .014686{col 37}{space 1}   19.58{col 46}{space 3}0.000{col 54}{space 4}  .258731{col 67}{space 3} .3163414
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3  if passed == 1 & (intentions == 1 & affective == 0 | intentions == 0 & affective == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       715
{txt}{hline 13}{c +}{hline 34}   F(2, 712)       = {res}     6.98
{txt}       Model {c |} {res} 1.31239732         2  .656198662   {txt}Prob > F        ={res}    0.0010
{txt}    Residual {c |} {res} 66.9569584       712  .094040672   {txt}R-squared       ={res}    0.0192
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0165
{txt}       Total {c |} {res} 68.2693557       714  .095615344   {txt}Root MSE        =   {res} .30666

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0551405{col 26}{space 2} .0229396{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4} .0101031{col 67}{space 3} .1001779
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0655226{col 26}{space 2} .0229375{col 37}{space 1}    2.86{col 46}{space 3}0.004{col 54}{space 4} .0204894{col 67}{space 3} .1105558
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2746236{col 26}{space 2} .0200048{col 37}{space 1}   13.73{col 46}{space 3}0.000{col 54}{space 4} .2353481{col 67}{space 3}  .313899
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *Competence*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (intentions == 0 & affective == 1 | intentions == 1 & affective == 0)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,008
{txt}{hline 13}{c +}{hline 34}   F(2, 1005)      = {res}     7.40
{txt}       Model {c |} {res}  .88430868         2   .44215434   {txt}Prob > F        ={res}    0.0006
{txt}    Residual {c |} {res} 60.0794803     1,005  .059780577   {txt}R-squared       ={res}    0.0145
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0125
{txt}       Total {c |} {res}  60.963789     1,007  .060540009   {txt}Root MSE        =   {res}  .2445

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0059426{col 36}{space 2}  .015405{col 47}{space 1}    0.39{col 56}{space 3}0.700{col 64}{space 4} -.024287{col 77}{space 3} .0361723
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0588541{col 36}{space 2} .0154096{col 47}{space 1}   -3.82{col 56}{space 3}0.000{col 64}{space 4}-.0890928{col 77}{space 3}-.0286154
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3889282{col 36}{space 2} .0135017{col 47}{space 1}   28.81{col 56}{space 3}0.000{col 64}{space 4} .3624334{col 77}{space 3} .4154229
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. gen att_competence = .
{txt}(4,335 missing values generated)

{com}. replace att_competence = dril_attitude if intentions == 0
{txt}(1,773 real changes made)

{com}. replace att_competence = air_attitude if intentions == 1
{txt}(1,138 real changes made)

{com}. 
. reg att_competence Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,637
{txt}{hline 13}{c +}{hline 34}   F(5, 1631)      = {res}   211.52
{txt}       Model {c |} {res} 71.9959718         5  14.3991944   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 111.030599     1,631  .068075168   {txt}R-squared       ={res}    0.3934
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3915
{txt}       Total {c |} {res} 183.026571     1,636  .111874432   {txt}Root MSE        =   {res} .26091

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}att_compet~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3992889{col 26}{space 2} .0225057{col 37}{space 1}   17.74{col 46}{space 3}0.000{col 54}{space 4} .3551459{col 67}{space 3} .4434319
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2} .0040904{col 26}{space 2} .0166013{col 37}{space 1}    0.25{col 46}{space 3}0.805{col 54}{space 4}-.0284717{col 67}{space 3} .0366525
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0294996{col 26}{space 2} .0166248{col 37}{space 1}   -1.77{col 46}{space 3}0.076{col 54}{space 4}-.0621078{col 67}{space 3} .0031085
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0756628{col 26}{space 2} .0263994{col 37}{space 1}    2.87{col 46}{space 3}0.004{col 54}{space 4} .0238825{col 67}{space 3}  .127443
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0183523{col 26}{space 2} .0263894{col 37}{space 1}   -0.70{col 46}{space 3}0.487{col 54}{space 4}-.0701129{col 67}{space 3} .0334084
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2490075{col 26}{space 2} .0142324{col 37}{space 1}   17.50{col 46}{space 3}0.000{col 54}{space 4} .2210918{col 67}{space 3} .2769232
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3  if passed == 1 & (intentions == 1 & affective == 1 | intentions == 0 & affective == 0)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       671
{txt}{hline 13}{c +}{hline 34}   F(2, 668)       = {res}     7.33
{txt}       Model {c |} {res} 1.37997898         2  .689989488   {txt}Prob > F        ={res}    0.0007
{txt}    Residual {c |} {res} 62.8930164       668  .094151222   {txt}R-squared       ={res}    0.0215
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0185
{txt}       Total {c |} {res} 64.2729954       670  .095929844   {txt}Root MSE        =   {res} .30684

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0654797{col 26}{space 2} .0236969{col 37}{space 1}    2.76{col 46}{space 3}0.006{col 54}{space 4} .0189504{col 67}{space 3}  .112009
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0613134{col 26}{space 2} .0236971{col 37}{space 1}    2.59{col 46}{space 3}0.010{col 54}{space 4} .0147837{col 67}{space 3} .1078432
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2799056{col 26}{space 2}  .020387{col 37}{space 1}   13.73{col 46}{space 3}0.000{col 54}{space 4} .2398752{col 67}{space 3}  .319936
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **Drilling-air traffic controllers**
. 
. *Drilling*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & affective == 0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       976
{txt}{hline 13}{c +}{hline 34}   F(2, 973)       = {res}    11.52
{txt}       Model {c |} {res} 1.30599142         2  .652995712   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  55.150935       973  .056681331   {txt}R-squared       ={res}    0.0231
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0211
{txt}       Total {c |} {res} 56.4569264       975   .05790454   {txt}Root MSE        =   {res} .23808

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0207073{col 36}{space 2} .0152437{col 47}{space 1}   -1.36{col 56}{space 3}0.175{col 64}{space 4}-.0506216{col 77}{space 3} .0092071
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0705307{col 36}{space 2} .0152488{col 47}{space 1}   -4.63{col 56}{space 3}0.000{col 64}{space 4}-.1004551{col 77}{space 3}-.0406064
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .4103311{col 36}{space 2}  .013366{col 47}{space 1}   30.70{col 56}{space 3}0.000{col 64}{space 4} .3841015{col 77}{space 3} .4365607
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg dril_attitude Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,653
{txt}{hline 13}{c +}{hline 34}   F(5, 1647)      = {res}   293.89
{txt}       Model {c |} {res}  97.530114         5  19.5060228   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 109.314308     1,647  .066371772   {txt}R-squared       ={res}    0.4715
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4699
{txt}       Total {c |} {res} 206.844422     1,652  .125208488   {txt}Root MSE        =   {res} .25763

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}dril_attit~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .4380357{col 26}{space 2} .0220909{col 37}{space 1}   19.83{col 46}{space 3}0.000{col 54}{space 4} .3947064{col 67}{space 3}  .481365
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0108631{col 26}{space 2} .0163437{col 37}{space 1}   -0.66{col 46}{space 3}0.506{col 54}{space 4}-.0429198{col 67}{space 3} .0211936
{txt}low_or_high2 {c |}{col 14}{res}{space 2} -.050674{col 26}{space 2} .0163655{col 37}{space 1}   -3.10{col 46}{space 3}0.002{col 54}{space 4}-.0827734{col 67}{space 3}-.0185746
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .0982056{col 26}{space 2} .0259133{col 37}{space 1}    3.79{col 46}{space 3}0.000{col 54}{space 4}  .047379{col 67}{space 3} .1490321
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} .0160445{col 26}{space 2} .0259065{col 37}{space 1}    0.62{col 46}{space 3}0.536{col 54}{space 4}-.0347687{col 67}{space 3} .0668576
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2458108{col 26}{space 2} .0140211{col 37}{space 1}   17.53{col 46}{space 3}0.000{col 54}{space 4} .2183097{col 67}{space 3} .2733119
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & affective == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       688
{txt}{hline 13}{c +}{hline 34}   F(2, 685)       = {res}     8.64
{txt}       Model {c |} {res} 1.56178645         2  .780893227   {txt}Prob > F        ={res}    0.0002
{txt}    Residual {c |} {res} 61.9257658       685  .090402578   {txt}R-squared       ={res}    0.0246
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0218
{txt}       Total {c |} {res} 63.4875522       687   .09241274   {txt}Root MSE        =   {res} .30067

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}  .049759{col 26}{space 2} .0229432{col 37}{space 1}    2.17{col 46}{space 3}0.030{col 54}{space 4} .0047115{col 67}{space 3} .0948065
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2}  .079409{col 26}{space 2} .0229439{col 37}{space 1}    3.46{col 46}{space 3}0.001{col 54}{space 4} .0343602{col 67}{space 3} .1244579
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2535701{col 26}{space 2} .0195939{col 37}{space 1}   12.94{col 46}{space 3}0.000{col 54}{space 4} .2150988{col 67}{space 3} .2920414
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. 
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *air traffic*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & affective == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       982
{txt}{hline 13}{c +}{hline 34}   F(2, 979)       = {res}     7.86
{txt}       Model {c |} {res} .902912193         2  .451456096   {txt}Prob > F        ={res}    0.0004
{txt}    Residual {c |} {res} 56.2104841       979  .057416225   {txt}R-squared       ={res}    0.0158
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0138
{txt}       Total {c |} {res} 57.1133963       981  .058219568   {txt}Root MSE        =   {res} .23962

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0204513{col 36}{space 2} .0153016{col 47}{space 1}    1.34{col 56}{space 3}0.182{col 64}{space 4}-.0095764{col 77}{space 3} .0504789
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0575198{col 36}{space 2} .0152967{col 47}{space 1}   -3.76{col 56}{space 3}0.000{col 64}{space 4} -.087538{col 77}{space 3}-.0275017
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3617922{col 36}{space 2}  .013078{col 47}{space 1}   27.66{col 56}{space 3}0.000{col 64}{space 4} .3361281{col 77}{space 3} .3874564
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg air_attitude Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,629
{txt}{hline 13}{c +}{hline 34}   F(5, 1623)      = {res}   114.73
{txt}       Model {c |} {res} 39.9153601         5  7.98307202   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 112.934239     1,623  .069583634   {txt}R-squared       ={res}    0.2611
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2589
{txt}       Total {c |} {res} 152.849599     1,628   .09388796   {txt}Root MSE        =   {res} .26379

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}air_attitude{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .2719753{col 26}{space 2} .0227986{col 37}{space 1}   11.93{col 46}{space 3}0.000{col 54}{space 4} .2272575{col 67}{space 3} .3166932
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0024339{col 26}{space 2} .0168629{col 37}{space 1}   -0.14{col 46}{space 3}0.885{col 54}{space 4}-.0355093{col 67}{space 3} .0306415
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0438222{col 26}{space 2} .0168824{col 37}{space 1}   -2.60{col 46}{space 3}0.010{col 54}{space 4}-.0769357{col 67}{space 3}-.0107087
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2}  .120078{col 26}{space 2} .0267241{col 37}{space 1}    4.49{col 46}{space 3}0.000{col 54}{space 4} .0676607{col 67}{space 3} .1724953
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2}-.0363984{col 26}{space 2} .0267202{col 37}{space 1}   -1.36{col 46}{space 3}0.173{col 54}{space 4}-.0888081{col 67}{space 3} .0160113
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2909211{col 26}{space 2} .0145073{col 37}{space 1}   20.05{col 46}{space 3}0.000{col 54}{space 4} .2624661{col 67}{space 3} .3193762
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & affective == 0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       698
{txt}{hline 13}{c +}{hline 34}   F(2, 695)       = {res}     6.26
{txt}       Model {c |} {res} 1.21085099         2  .605425495   {txt}Prob > F        ={res}    0.0020
{txt}    Residual {c |} {res} 67.2353775       695   .09674155   {txt}R-squared       ={res}    0.0177
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0149
{txt}       Total {c |} {res} 68.4462285       697  .098201189   {txt}Root MSE        =   {res} .31103

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0694908{col 26}{space 2} .0235484{col 37}{space 1}    2.95{col 46}{space 3}0.003{col 54}{space 4} .0232563{col 67}{space 3} .1157254
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0469647{col 26}{space 2} .0235542{col 37}{space 1}    1.99{col 46}{space 3}0.047{col 54}{space 4} .0007188{col 67}{space 3} .0932107
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3015697{col 26}{space 2} .0206901{col 37}{space 1}   14.58{col 46}{space 3}0.000{col 54}{space 4}  .260947{col 67}{space 3} .3421923
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. 
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **Independents-partisans - what drives effects on trust?**
. 
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & partyid == 4

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       272
{txt}{hline 13}{c +}{hline 34}   F(2, 269)       = {res}     1.17
{txt}       Model {c |} {res} .133058054         2  .066529027   {txt}Prob > F        ={res}    0.3107
{txt}    Residual {c |} {res} 15.2438954       269  .056668756   {txt}R-squared       ={res}    0.0087
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0013
{txt}       Total {c |} {res} 15.3769534       271  .056741526   {txt}Root MSE        =   {res} .23805

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0006836{col 36}{space 2} .0290045{col 47}{space 1}    0.02{col 56}{space 3}0.981{col 64}{space 4}-.0564211{col 77}{space 3} .0577884
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.044321{col 36}{space 2} .0290045{col 47}{space 1}   -1.53{col 56}{space 3}0.128{col 64}{space 4}-.1014258{col 77}{space 3} .0127837
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3177898{col 36}{space 2} .0243281{col 47}{space 1}   13.06{col 56}{space 3}0.000{col 64}{space 4} .2698921{col 77}{space 3} .3656876
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pure_independents
{txt}
{com}. 
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (partyid == 4 | partyid == 3 | partyid == 5)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       785
{txt}{hline 13}{c +}{hline 34}   F(2, 782)       = {res}    10.14
{txt}       Model {c |} {res} 1.04929564         2  .524647818   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 40.4673595       782  .051748542   {txt}R-squared       ={res}    0.0253
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0228
{txt}       Total {c |} {res} 41.5166552       784  .052954917   {txt}Root MSE        =   {res} .22748

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0112489{col 36}{space 2} .0162504{col 47}{space 1}    0.69{col 56}{space 3}0.489{col 64}{space 4}-.0206506{col 77}{space 3} .0431485
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.072646{col 36}{space 2} .0162492{col 47}{space 1}   -4.47{col 56}{space 3}0.000{col 64}{space 4}-.1045433{col 77}{space 3}-.0407487
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3509799{col 36}{space 2} .0138838{col 47}{space 1}   25.28{col 56}{space 3}0.000{col 64}{space 4} .3237259{col 77}{space 3} .3782339
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Ind_incl_leaners
{txt}
{com}. 
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (partyid == 1 | partyid == 2 | partyid == 3 | partyid == 5 | partyid == 6 | partyid == 7)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,612
{txt}{hline 13}{c +}{hline 34}   F(2, 1609)      = {res}    15.99
{txt}       Model {c |} {res} 1.78277835         2  .891389176   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 89.7065615     1,609   .05575299   {txt}R-squared       ={res}    0.0195
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0183
{txt}       Total {c |} {res} 91.4893398     1,611  .056790403   {txt}Root MSE        =   {res} .23612

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0028757{col 36}{space 2} .0117693{col 47}{space 1}    0.24{col 56}{space 3}0.807{col 64}{space 4}-.0202091{col 77}{space 3} .0259605
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0664251{col 36}{space 2} .0117661{col 47}{space 1}   -5.65{col 56}{space 3}0.000{col 64}{space 4}-.0895037{col 77}{space 3}-.0433466
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .4041768{col 36}{space 2}  .010206{col 47}{space 1}   39.60{col 56}{space 3}0.000{col 64}{space 4} .3841583{col 77}{space 3} .4241952
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Partisans_incl_leaners
{txt}
{com}. 
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (partyid == 1 | partyid == 2 | partyid == 6 | partyid == 7)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,099
{txt}{hline 13}{c +}{hline 34}   F(2, 1096)      = {res}     7.25
{txt}       Model {c |} {res} .840851345         2  .420425672   {txt}Prob > F        ={res}    0.0007
{txt}    Residual {c |} {res}  63.544815     1,096  .057978846   {txt}R-squared       ={res}    0.0131
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0113
{txt}       Total {c |} {res} 64.3856663     1,098   .05863904   {txt}Root MSE        =   {res} .24079

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0044069{col 36}{space 2}  .014536{col 47}{space 1}   -0.30{col 56}{space 3}0.762{col 64}{space 4}-.0329284{col 77}{space 3} .0241146
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0552586{col 36}{space 2} .0145326{col 47}{space 1}   -3.80{col 56}{space 3}0.000{col 64}{space 4}-.0837736{col 77}{space 3}-.0267436
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .4203294{col 36}{space 2} .0126411{col 47}{space 1}   33.25{col 56}{space 3}0.000{col 64}{space 4} .3955258{col 77}{space 3}  .445133
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Partisans_excl_leaners
{txt}
{com}. 
. *figure*
. coefplot Pure_independents Ind_incl_leaners Partisans_incl_leaners Partisans_excl_leaners, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12) legend(cols(1))
{res}{txt}
{com}. 
. **Democrats vs. Republicans**
. 
. *Democrats*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & Dem0 == 0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       967
{txt}{hline 13}{c +}{hline 34}   F(2, 964)       = {res}     5.71
{txt}       Model {c |} {res} .622804017         2  .311402008   {txt}Prob > F        ={res}    0.0034
{txt}    Residual {c |} {res} 52.5345931       964  .054496466   {txt}R-squared       ={res}    0.0117
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0097
{txt}       Total {c |} {res} 53.1573971       966  .055028361   {txt}Root MSE        =   {res} .23344

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0052721{col 36}{space 2} .0150398{col 47}{space 1}    0.35{col 56}{space 3}0.726{col 64}{space 4}-.0242424{col 77}{space 3} .0347867
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0504543{col 36}{space 2} .0150277{col 47}{space 1}   -3.36{col 56}{space 3}0.001{col 64}{space 4}-.0799451{col 77}{space 3}-.0209635
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3633181{col 36}{space 2} .0130088{col 47}{space 1}   27.93{col 56}{space 3}0.000{col 64}{space 4} .3377893{col 77}{space 3} .3888469
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index civility2 low_or_high2 if passed == 1 & Dem0 == 0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       954
{txt}{hline 13}{c +}{hline 34}   F(2, 951)       = {res}     6.69
{txt}       Model {c |} {res} .572877201         2  .286438601   {txt}Prob > F        ={res}    0.0013
{txt}    Residual {c |} {res} 40.7090939       951  .042806618   {txt}R-squared       ={res}    0.0139
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0118
{txt}       Total {c |} {res} 41.2819711       953  .043317913   {txt}Root MSE        =   {res}  .2069

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility2 {c |}{col 14}{res}{space 2}-.0039481{col 26}{space 2} .0134078{col 37}{space 1}   -0.29{col 46}{space 3}0.768{col 54}{space 4}-.0302603{col 67}{space 3} .0223641
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0489404{col 26}{space 2} .0134219{col 37}{space 1}   -3.65{col 46}{space 3}0.000{col 54}{space 4}-.0752805{col 67}{space 3}-.0226004
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2676977{col 26}{space 2} .0115396{col 37}{space 1}   23.20{col 46}{space 3}0.000{col 54}{space 4} .2450516{col 67}{space 3} .2903437
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & Dem0 == 0

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       836
{txt}{hline 13}{c +}{hline 34}   F(2, 833)       = {res}     6.64
{txt}       Model {c |} {res} 1.24458498         2   .62229249   {txt}Prob > F        ={res}    0.0014
{txt}    Residual {c |} {res}  78.057699       833  .093706722   {txt}R-squared       ={res}    0.0157
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0133
{txt}       Total {c |} {res}  79.302284       835  .094972795   {txt}Root MSE        =   {res} .30612

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0558063{col 26}{space 2} .0211748{col 37}{space 1}    2.64{col 46}{space 3}0.009{col 54}{space 4} .0142442{col 67}{space 3} .0973685
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0530462{col 26}{space 2} .0211796{col 37}{space 1}    2.50{col 46}{space 3}0.012{col 54}{space 4} .0114746{col 67}{space 3} .0946179
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3206695{col 26}{space 2} .0184569{col 37}{space 1}   17.37{col 46}{space 3}0.000{col 54}{space 4} .2844421{col 67}{space 3}  .356897
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. coefplot Pooled Pooled2 Pooled3, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" civility2="{c -(}bf:Effects on pol. attitudes{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *Republicans*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & Dem0 == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       645
{txt}{hline 13}{c +}{hline 34}   F(2, 642)       = {res}    11.13
{txt}       Model {c |} {res} 1.20166906         2  .600834528   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 34.6471149       642  .053967469   {txt}R-squared       ={res}    0.0335
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0305
{txt}       Total {c |} {res}  35.848784       644  .055665814   {txt}Root MSE        =   {res} .23231

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0064612{col 36}{space 2} .0182963{col 47}{space 1}   -0.35{col 56}{space 3}0.724{col 64}{space 4} -.042389{col 77}{space 3} .0294666
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0861751{col 36}{space 2} .0182963{col 47}{space 1}   -4.71{col 56}{space 3}0.000{col 64}{space 4}-.1221029{col 77}{space 3}-.0502473
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .4658033{col 36}{space 2}  .015918{col 47}{space 1}   29.26{col 56}{space 3}0.000{col 64}{space 4} .4345457{col 77}{space 3}  .497061
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. reg att_index civility2 low_or_high2 if passed == 1 & Dem0 == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       634
{txt}{hline 13}{c +}{hline 34}   F(2, 631)       = {res}     6.43
{txt}       Model {c |} {res} .670547828         2  .335273914   {txt}Prob > F        ={res}    0.0017
{txt}    Residual {c |} {res}  32.911031       631  .052156943   {txt}R-squared       ={res}    0.0200
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0169
{txt}       Total {c |} {res} 33.5815788       633  .053051467   {txt}Root MSE        =   {res} .22838

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}civility2 {c |}{col 14}{res}{space 2}-.0220551{col 26}{space 2} .0181534{col 37}{space 1}   -1.21{col 46}{space 3}0.225{col 54}{space 4}-.0577034{col 67}{space 3} .0135932
{txt}low_or_high2 {c |}{col 14}{res}{space 2} .0618262{col 26}{space 2} .0181479{col 37}{space 1}    3.41{col 46}{space 3}0.001{col 54}{space 4} .0261886{col 67}{space 3} .0974639
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6300091{col 26}{space 2} .0154697{col 37}{space 1}   40.73{col 46}{space 3}0.000{col 54}{space 4} .5996308{col 67}{space 3} .6603874
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3 if passed == 1 & Dem0 == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       550
{txt}{hline 13}{c +}{hline 34}   F(2, 547)       = {res}     7.99
{txt}       Model {c |} {res} 1.43290296         2  .716451478   {txt}Prob > F        ={res}    0.0004
{txt}    Residual {c |} {res} 49.0432836       547  .089658654   {txt}R-squared       ={res}    0.0284
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0248
{txt}       Total {c |} {res} 50.4761865       549  .091942052   {txt}Root MSE        =   {res} .29943

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0676632{col 26}{space 2} .0255445{col 37}{space 1}    2.65{col 46}{space 3}0.008{col 54}{space 4}  .017486{col 67}{space 3} .1178405
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0749771{col 26}{space 2}  .025546{col 37}{space 1}    2.93{col 46}{space 3}0.003{col 54}{space 4} .0247969{col 67}{space 3} .1251573
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2129815{col 26}{space 2} .0219321{col 37}{space 1}    9.71{col 46}{space 3}0.000{col 54}{space 4}    .1699{col 67}{space 3} .2560629
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. coefplot Pooled Pooled2 Pooled3, drop(_cons) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" civility2="{c -(}bf:Effects on pol. attitudes{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. **DV after first or second issue**
. 
. *first*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (order == 1 & affective == 1 | order == 0 & affective == 0)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       997
{txt}{hline 13}{c +}{hline 34}   F(2, 994)       = {res}    17.62
{txt}       Model {c |} {res} 1.97415187         2  .987075934   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 55.6704749       994  .056006514   {txt}R-squared       ={res}    0.0342
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0323
{txt}       Total {c |} {res} 57.6446267       996  .057876131   {txt}Root MSE        =   {res} .23666

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2} .0124013{col 36}{space 2} .0149987{col 47}{space 1}    0.83{col 56}{space 3}0.409{col 64}{space 4}-.0170315{col 77}{space 3}  .041834
{txt}civility_or_incivility {c |}{col 24}{res}{space 2} -.087767{col 36}{space 2} .0150021{col 47}{space 1}   -5.85{col 56}{space 3}0.000{col 64}{space 4}-.1172065{col 77}{space 3}-.0583275
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3790865{col 36}{space 2} .0129553{col 47}{space 1}   29.26{col 56}{space 3}0.000{col 64}{space 4} .3536635{col 77}{space 3} .4045094
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. gen att_first = .
{txt}(4,335 missing values generated)

{com}. replace att_first = dril_attitude if order == 1
{txt}(1,485 real changes made)

{com}. replace att_first = air_attitude if order == 0
{txt}(1,468 real changes made)

{com}. 
. reg att_first Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,655
{txt}{hline 13}{c +}{hline 34}   F(5, 1649)      = {res}   196.58
{txt}       Model {c |} {res} 65.6377886         5  13.1275577   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 110.119409     1,649  .066779508   {txt}R-squared       ={res}    0.3735
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3716
{txt}       Total {c |} {res} 175.757198     1,654  .106261909   {txt}Root MSE        =   {res} .25842

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_first{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3434588{col 26}{space 2} .0220314{col 37}{space 1}   15.59{col 46}{space 3}0.000{col 54}{space 4} .3002463{col 67}{space 3} .3866714
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0130505{col 26}{space 2} .0163791{col 37}{space 1}   -0.80{col 46}{space 3}0.426{col 54}{space 4}-.0451766{col 67}{space 3} .0190756
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0459141{col 26}{space 2} .0164018{col 37}{space 1}   -2.80{col 46}{space 3}0.005{col 54}{space 4}-.0780847{col 67}{space 3}-.0137436
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2} .1116762{col 26}{space 2}  .025988{col 37}{space 1}    4.30{col 46}{space 3}0.000{col 54}{space 4} .0607033{col 67}{space 3} .1626491
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} .0102097{col 26}{space 2} .0259872{col 37}{space 1}    0.39{col 46}{space 3}0.694{col 54}{space 4}-.0407616{col 67}{space 3} .0611811
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2818549{col 26}{space 2} .0140235{col 37}{space 1}   20.10{col 46}{space 3}0.000{col 54}{space 4} .2543491{col 67}{space 3} .3093606
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3  if passed == 1 & (order == 1 & affective == 0 | order == 0 & affective == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       698
{txt}{hline 13}{c +}{hline 34}   F(2, 695)       = {res}    10.22
{txt}       Model {c |} {res} 1.85409174         2   .92704587   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 63.0679483       695  .090745249   {txt}R-squared       ={res}    0.0286
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0258
{txt}       Total {c |} {res} 64.9220401       697  .093144964   {txt}Root MSE        =   {res} .30124

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2}  .074964{col 26}{space 2} .0228423{col 37}{space 1}    3.28{col 46}{space 3}0.001{col 54}{space 4} .0301157{col 67}{space 3} .1198123
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0670271{col 26}{space 2} .0228778{col 37}{space 1}    2.93{col 46}{space 3}0.004{col 54}{space 4} .0221092{col 67}{space 3}  .111945
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .271541{col 26}{space 2} .0196785{col 37}{space 1}   13.80{col 46}{space 3}0.000{col 54}{space 4} .2329044{col 67}{space 3} .3101775
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. *second*
. 
. *trust*
. reg trust_index low_or_high_issue_pol civility_or_incivility if passed == 1 & (order == 1 & affective == 0 | order == 0 & affective == 1)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       961
{txt}{hline 13}{c +}{hline 34}   F(2, 958)       = {res}     3.68
{txt}       Model {c |} {res} .426653444         2  .213326722   {txt}Prob > F        ={res}    0.0255
{txt}    Residual {c |} {res} 55.4779694       958  .057910198   {txt}R-squared       ={res}    0.0076
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0056
{txt}       Total {c |} {res} 55.9046229       960  .058233982   {txt}Root MSE        =   {res} .24065

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           trust_index{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}low_or_high_issue_pol {c |}{col 24}{res}{space 2}-.0138542{col 36}{space 2} .0155396{col 47}{space 1}   -0.89{col 56}{space 3}0.373{col 64}{space 4}-.0443498{col 77}{space 3} .0166413
{txt}civility_or_incivility {c |}{col 24}{res}{space 2}-.0393549{col 36}{space 2} .0155659{col 47}{space 1}   -2.53{col 56}{space 3}0.012{col 64}{space 4}-.0699021{col 77}{space 3}-.0088076
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} .3921832{col 36}{space 2} .0134819{col 47}{space 1}   29.09{col 56}{space 3}0.000{col 64}{space 4} .3657257{col 77}{space 3} .4186406
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled
{txt}
{com}. 
. *attitude polarization*
. gen att_second = .
{txt}(4,335 missing values generated)

{com}. replace att_second = dril_attitude if order == 0
{txt}(1,468 real changes made)

{com}. replace att_second = air_attitude if order == 1
{txt}(1,441 real changes made)

{com}. 
. reg att_second Dem0Rep1 civility2 low_or_high2 pol_party civ_party if passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,627
{txt}{hline 13}{c +}{hline 34}   F(5, 1621)      = {res}   178.36
{txt}       Model {c |} {res} 65.2574689         5  13.0514938   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 118.618238     1,621  .073175964   {txt}R-squared       ={res}    0.3549
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3529
{txt}       Total {c |} {res} 183.875707     1,626   .11308469   {txt}Root MSE        =   {res} .27051

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  att_second{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}Dem0Rep1 {c |}{col 14}{res}{space 2} .3683022{col 26}{space 2} .0235188{col 37}{space 1}   15.66{col 46}{space 3}0.000{col 54}{space 4} .3221717{col 67}{space 3} .4144327
{txt}{space 3}civility2 {c |}{col 14}{res}{space 2}-.0001995{col 26}{space 2} .0173098{col 37}{space 1}   -0.01{col 46}{space 3}0.991{col 54}{space 4}-.0341515{col 67}{space 3} .0337525
{txt}low_or_high2 {c |}{col 14}{res}{space 2}-.0483191{col 26}{space 2}  .017329{col 37}{space 1}   -2.79{col 46}{space 3}0.005{col 54}{space 4}-.0823087{col 67}{space 3}-.0143295
{txt}{space 3}pol_party {c |}{col 14}{res}{space 2}  .105418{col 26}{space 2} .0274123{col 37}{space 1}    3.85{col 46}{space 3}0.000{col 54}{space 4} .0516508{col 67}{space 3} .1591852
{txt}{space 3}civ_party {c |}{col 14}{res}{space 2} -.029731{col 26}{space 2} .0274034{col 37}{space 1}   -1.08{col 46}{space 3}0.278{col 54}{space 4}-.0834809{col 67}{space 3} .0240189
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2541335{col 26}{space 2} .0149217{col 37}{space 1}   17.03{col 46}{space 3}0.000{col 54}{space 4} .2248657{col 67}{space 3} .2834012
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled2
{txt}
{com}. 
. *affective polarization*
. reg afpol_index low_or_high3 civility3  if passed == 1 & (order == 1 & affective == 1 | order == 0 & affective == 0)

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       688
{txt}{hline 13}{c +}{hline 34}   F(2, 685)       = {res}     4.62
{txt}       Model {c |} {res}  .90051185         2  .450255925   {txt}Prob > F        ={res}    0.0101
{txt}    Residual {c |} {res} 66.7145447       685  .097393496   {txt}R-squared       ={res}    0.0133
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0104
{txt}       Total {c |} {res} 67.6150566       687  .098420752   {txt}Root MSE        =   {res} .31208

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} afpol_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
low_or_high3 {c |}{col 14}{res}{space 2} .0450046{col 26}{space 2} .0238217{col 37}{space 1}    1.89{col 46}{space 3}0.059{col 54}{space 4}-.0017677{col 67}{space 3} .0917769
{txt}{space 3}civility3 {c |}{col 14}{res}{space 2} .0579933{col 26}{space 2} .0238338{col 37}{space 1}    2.43{col 46}{space 3}0.015{col 54}{space 4} .0111972{col 67}{space 3} .1047893
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2840788{col 26}{space 2} .0207439{col 37}{space 1}   13.69{col 46}{space 3}0.000{col 54}{space 4} .2433496{col 67}{space 3} .3248081
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store Pooled3
{txt}
{com}. 
. *figure*
. coefplot Pooled Pooled2 Pooled3, drop(_cons Dem0Rep1 civility2 low_or_high2) scheme(s1mono) xline(0, lcolor(gray)) msymbol(circle) ///
> xscale(range(-0.23 0.23)) xlabel(-0.20 -0.10 0.00 0.10 0.20) levels(95 90) ///
> headings(low_or_high_issue_pol="{c -(}bf:Effects on trust in politicians{c )-}" pol_party="{c -(}bf:Effects on attitude polarization{c )-}" low_or_high3="{c -(}bf:Effects on affective polarization{c )-}", labgap(-130)) legend(off) ///
> yscale(alt) coeflabels(, notick labgap(-125)) graphregion(margin(l=65)) grid(none) format(%9.1g) mlabel mlabposition(12)
{res}{txt}
{com}. 
. *changing color of markers*
. gr_edit plotregion1.plot3.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot3.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot6.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(fillcolor(black)) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot9.style.editstyle marker(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 90 percent intervals*
. gr_edit plotregion1.plot1.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot4.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot7.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of 95 percent intervals*
. gr_edit plotregion1.plot2.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot5.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. gr_edit plotregion1.plot8.style.editstyle area(linestyle(color(black))) editcopy
{res}{txt}
{com}. 
. *changing color of zero line*
. gr_edit plotregion1._xylines[1].style.editstyle linestyle(color(black)) editcopy
{res}{txt}
{com}. 
. ***Appendix A12***
. 
. *Trust*
. 
. mean trust_index if passed == 1, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}     2,431

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.trust_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .3866072{col 43}{space 2} .0110433{col 54}{space 5} .3649518{col 68}{space 3} .4082625
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2} .3207921{col 43}{space 2} .0101989{col 54}{space 5} .3007927{col 68}{space 3} .3407915
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .3844015{col 43}{space 2} .0115015{col 54}{space 5} .3618478{col 68}{space 3} .4069552
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .3234471{col 43}{space 2} .0105369{col 54}{space 5} .3027848{col 68}{space 3} .3441094
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .3020613{col 43}{space 2} .0113627{col 54}{space 5} .2797798{col 68}{space 3} .3243429
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.40)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
. mean trust_index if passed == 1 & sample == 1, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}     1,124

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.trust_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .3859305{col 43}{space 2} .0168466{col 54}{space 5} .3528762{col 68}{space 3} .4189849
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2} .3389423{col 43}{space 2} .0157461{col 54}{space 5} .3080471{col 68}{space 3} .3698375
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .3775077{col 43}{space 2} .0177226{col 54}{space 5} .3427347{col 68}{space 3} .4122808
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .3288752{col 43}{space 2}  .014923{col 54}{space 5} .2995951{col 68}{space 3} .3581553
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .2867588{col 43}{space 2} .0176123{col 54}{space 5} .2522021{col 68}{space 3} .3213155
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.40)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
. mean trust_index if passed == 1 & sample == 2, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}     1,307

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.trust_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .3871723{col 43}{space 2} .0146156{col 54}{space 5} .3584997{col 68}{space 3} .4158449
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2} .3051199{col 43}{space 2} .0132328{col 54}{space 5} .2791602{col 68}{space 3} .3310797
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .3902181{col 43}{space 2} .0150587{col 54}{space 5} .3606763{col 68}{space 3}   .41976
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .3181284{col 43}{space 2} .0149014{col 54}{space 5} .2888951{col 68}{space 3} .3473616
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .3140723{col 43}{space 2}  .014828{col 54}{space 5}  .284983{col 68}{space 3} .3431617
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.40)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
. *Attitude polarization*
. 
. regress att_index De1 if treatment == 1 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       409
{txt}{hline 13}{c +}{hline 34}   F(1, 407)       = {res}   292.64
{txt}       Model {c |} {res} 12.5357569         1  12.5357569   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 17.4347668       407  .042837265   {txt}R-squared       ={res}    0.4183
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4168
{txt}       Total {c |} {res} 29.9705237       408  .073457166   {txt}Root MSE        =   {res} .20697

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De1 {c |}{col 14}{res}{space 2} .3565166{col 26}{space 2} .0208408{col 37}{space 1}   17.11{col 46}{space 3}0.000{col 54}{space 4} .3155475{col 67}{space 3} .3974857
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2740055{col 26}{space 2} .0132772{col 37}{space 1}   20.64{col 46}{space 3}0.000{col 54}{space 4}  .247905{col 67}{space 3}  .300106
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R1
{txt}
{com}. regress att_index De2 if treatment == 2 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       412
{txt}{hline 13}{c +}{hline 34}   F(1, 410)       = {res}   247.83
{txt}       Model {c |} {res} 11.6156238         1  11.6156238   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 19.2167647       410  .046870158   {txt}R-squared       ={res}    0.3767
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3752
{txt}       Total {c |} {res} 30.8323885       411  .075017977   {txt}Root MSE        =   {res}  .2165

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De2 {c |}{col 14}{res}{space 2} .3494611{col 26}{space 2} .0221986{col 37}{space 1}   15.74{col 46}{space 3}0.000{col 54}{space 4} .3058238{col 67}{space 3} .3930984
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2579214{col 26}{space 2} .0133497{col 37}{space 1}   19.32{col 46}{space 3}0.000{col 54}{space 4} .2316791{col 67}{space 3} .2841638
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R2
{txt}
{com}. regress att_index De3 if treatment == 3 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       374
{txt}{hline 13}{c +}{hline 34}   F(1, 372)       = {res}   432.88
{txt}       Model {c |} {res} 21.0306404         1  21.0306404   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.0730613       372  .048583498   {txt}R-squared       ={res}    0.5378
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5366
{txt}       Total {c |} {res} 39.1037018       373  .104835662   {txt}Root MSE        =   {res} .22042

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De3 {c |}{col 14}{res}{space 2} .4796719{col 26}{space 2} .0230549{col 37}{space 1}   20.81{col 46}{space 3}0.000{col 54}{space 4} .4343377{col 67}{space 3} .5250061
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2116279{col 26}{space 2} .0150323{col 37}{space 1}   14.08{col 46}{space 3}0.000{col 54}{space 4}  .182069{col 67}{space 3} .2411868
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R3
{txt}
{com}. regress att_index De4 if treatment == 4 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       393
{txt}{hline 13}{c +}{hline 34}   F(1, 391)       = {res}   396.43
{txt}       Model {c |} {res} 19.1174755         1  19.1174755   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 18.8557352       391  .048224387   {txt}R-squared       ={res}    0.5034
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5022
{txt}       Total {c |} {res} 37.9732107       392  .096870435   {txt}Root MSE        =   {res}  .2196

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De4 {c |}{col 14}{res}{space 2} .4489248{col 26}{space 2} .0225472{col 37}{space 1}   19.91{col 46}{space 3}0.000{col 54}{space 4}  .404596{col 67}{space 3} .4932536
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2213877{col 26}{space 2} .0143865{col 37}{space 1}   15.39{col 46}{space 3}0.000{col 54}{space 4} .1931031{col 67}{space 3} .2496723
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R4
{txt}
{com}. regress att_index De5 if treatment == 5 & passed == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       376
{txt}{hline 13}{c +}{hline 34}   F(1, 374)       = {res}   211.42
{txt}       Model {c |} {res} 10.7811232         1  10.7811232   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 19.0715468       374  .050993441   {txt}R-squared       ={res}    0.3611
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3594
{txt}       Total {c |} {res}   29.85267       375   .07960712   {txt}Root MSE        =   {res} .22582

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De5 {c |}{col 14}{res}{space 2} .3502724{col 26}{space 2} .0240897{col 37}{space 1}   14.54{col 46}{space 3}0.000{col 54}{space 4} .3029042{col 67}{space 3} .3976406
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2634181{col 26}{space 2} .0146995{col 37}{space 1}   17.92{col 46}{space 3}0.000{col 54}{space 4} .2345141{col 67}{space 3}  .292322
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R5
{txt}
{com}. 
. coefplot R1 R2 R3 R4 R5, drop(_cons) vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.50)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4 0.5) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) offset(0.0) lcolor(black)
{res}{txt}
{com}. 
. regress att_index De1 if treatment == 1 & passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       190
{txt}{hline 13}{c +}{hline 34}   F(1, 188)       = {res}   161.21
{txt}       Model {c |} {res} 7.27329432         1  7.27329432   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.48200508       188  .045117048   {txt}R-squared       ={res}    0.4616
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4588
{txt}       Total {c |} {res} 15.7552994       189  .083361372   {txt}Root MSE        =   {res} .21241

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De1 {c |}{col 14}{res}{space 2} .3950241{col 26}{space 2}  .031112{col 37}{space 1}   12.70{col 46}{space 3}0.000{col 54}{space 4} .3336505{col 67}{space 3} .4563976
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2746914{col 26}{space 2} .0204389{col 37}{space 1}   13.44{col 46}{space 3}0.000{col 54}{space 4} .2343722{col 67}{space 3} .3150105
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R1
{txt}
{com}. regress att_index De2 if treatment == 2 & passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       183
{txt}{hline 13}{c +}{hline 34}   F(1, 181)       = {res}   127.63
{txt}       Model {c |} {res} 7.38455761         1  7.38455761   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 10.4727582       181  .057860542   {txt}R-squared       ={res}    0.4135
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4103
{txt}       Total {c |} {res} 17.8573158       182   .09811712   {txt}Root MSE        =   {res} .24054

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De2 {c |}{col 14}{res}{space 2} .4102325{col 26}{space 2} .0363127{col 37}{space 1}   11.30{col 46}{space 3}0.000{col 54}{space 4} .3385817{col 67}{space 3} .4818832
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2575758{col 26}{space 2} .0229348{col 37}{space 1}   11.23{col 46}{space 3}0.000{col 54}{space 4} .2123218{col 67}{space 3} .3028297
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R2
{txt}
{com}. regress att_index De3 if treatment == 3 & passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       170
{txt}{hline 13}{c +}{hline 34}   F(1, 168)       = {res}   288.18
{txt}       Model {c |} {res} 14.5537465         1  14.5537465   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.48448835       168  .050502907   {txt}R-squared       ={res}    0.6317
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.6295
{txt}       Total {c |} {res} 23.0382348       169  .136320916   {txt}Root MSE        =   {res} .22473

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De3 {c |}{col 14}{res}{space 2} .5852252{col 26}{space 2} .0344742{col 37}{space 1}   16.98{col 46}{space 3}0.000{col 54}{space 4} .5171668{col 67}{space 3} .6532836
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1686508{col 26}{space 2} .0245199{col 37}{space 1}    6.88{col 46}{space 3}0.000{col 54}{space 4}  .120244{col 67}{space 3} .2170576
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R3
{txt}
{com}. regress att_index De4 if treatment == 4 & passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       191
{txt}{hline 13}{c +}{hline 34}   F(1, 189)       = {res}   281.32
{txt}       Model {c |} {res} 13.7603688         1  13.7603688   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 9.24479335       189  .048914251   {txt}R-squared       ={res}    0.5981
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.5960
{txt}       Total {c |} {res} 23.0051622       190  .121079801   {txt}Root MSE        =   {res} .22117

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De4 {c |}{col 14}{res}{space 2} .5431163{col 26}{space 2} .0323814{col 37}{space 1}   16.77{col 46}{space 3}0.000{col 54}{space 4}  .479241{col 67}{space 3} .6069917
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1893939{col 26}{space 2} .0210873{col 37}{space 1}    8.98{col 46}{space 3}0.000{col 54}{space 4} .1477972{col 67}{space 3} .2309907
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R4
{txt}
{com}. regress att_index De5 if treatment == 5 & passed == 1 & sample == 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       156
{txt}{hline 13}{c +}{hline 34}   F(1, 154)       = {res}   100.24
{txt}       Model {c |} {res} 6.04745821         1  6.04745821   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 9.29103858       154  .060331419   {txt}R-squared       ={res}    0.3943
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3903
{txt}       Total {c |} {res} 15.3384968       155  .098958044   {txt}Root MSE        =   {res} .24562

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De5 {c |}{col 14}{res}{space 2}   .40348{col 26}{space 2} .0403002{col 37}{space 1}   10.01{col 46}{space 3}0.000{col 54}{space 4} .3238674{col 67}{space 3} .4830926
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2385965{col 26}{space 2} .0252005{col 37}{space 1}    9.47{col 46}{space 3}0.000{col 54}{space 4} .1888131{col 67}{space 3} .2883799
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R5
{txt}
{com}. 
. regress att_index De5 if passed == 1& sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,074
{txt}{hline 13}{c +}{hline 34}   F(1, 1072)      = {res}   659.44
{txt}       Model {c |} {res} 27.2125707         1  27.2125707   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 44.2376723     1,072  .041266485   {txt}R-squared       ={res}    0.3809
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3803
{txt}       Total {c |} {res}  71.450243     1,073  .066589229   {txt}Root MSE        =   {res} .20314

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De5 {c |}{col 14}{res}{space 2} .3308173{col 26}{space 2} .0128826{col 37}{space 1}   25.68{col 46}{space 3}0.000{col 54}{space 4} .3055394{col 67}{space 3} .3560952
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2606149{col 26}{space 2}  .007773{col 37}{space 1}   33.53{col 46}{space 3}0.000{col 54}{space 4} .2453629{col 67}{space 3} .2758669
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. coefplot R1 R2 R3 R4 R5, drop(_cons) vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.50)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4 0.5) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) offset(0.0) lcolor(black)
{res}{txt}
{com}. 
. regress att_index De1 if treatment == 1 & passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       219
{txt}{hline 13}{c +}{hline 34}   F(1, 217)       = {res}   131.21
{txt}       Model {c |} {res} 5.26283179         1  5.26283179   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.70374578       217  .040109428   {txt}R-squared       ={res}    0.3768
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3739
{txt}       Total {c |} {res} 13.9665776       218   .06406687   {txt}Root MSE        =   {res} .20027

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De1 {c |}{col 14}{res}{space 2} .3188051{col 26}{space 2} .0278316{col 37}{space 1}   11.45{col 46}{space 3}0.000{col 54}{space 4} .2639502{col 67}{space 3} .3736601
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2734568{col 26}{space 2} .0172368{col 37}{space 1}   15.86{col 46}{space 3}0.000{col 54}{space 4} .2394838{col 67}{space 3} .3074298
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R1
{txt}
{com}. regress att_index De2 if treatment == 2 & passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       229
{txt}{hline 13}{c +}{hline 34}   F(1, 227)       = {res}   118.86
{txt}       Model {c |} {res} 4.30496127         1  4.30496127   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.22142127       227  .036217715   {txt}R-squared       ={res}    0.3437
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3408
{txt}       Total {c |} {res} 12.5263825       228  .054940274   {txt}Root MSE        =   {res} .19031

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De2 {c |}{col 14}{res}{space 2} .2911722{col 26}{space 2}  .026707{col 37}{space 1}   10.90{col 46}{space 3}0.000{col 54}{space 4} .2385468{col 67}{space 3} .3437976
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2581699{col 26}{space 2} .0153856{col 37}{space 1}   16.78{col 46}{space 3}0.000{col 54}{space 4} .2278531{col 67}{space 3} .2884868
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R2
{txt}
{com}. regress att_index De3 if treatment == 3 & passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       204
{txt}{hline 13}{c +}{hline 34}   F(1, 202)       = {res}   157.65
{txt}       Model {c |} {res} 6.71201365         1  6.71201365   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.60045215       202  .042576496   {txt}R-squared       ={res}    0.4383
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4356
{txt}       Total {c |} {res} 15.3124658       203  .075430866   {txt}Root MSE        =   {res} .20634

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De3 {c |}{col 14}{res}{space 2} .3783942{col 26}{space 2} .0301372{col 37}{space 1}   12.56{col 46}{space 3}0.000{col 54}{space 4} .3189703{col 67}{space 3}  .437818
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2391858{col 26}{space 2} .0180281{col 37}{space 1}   13.27{col 46}{space 3}0.000{col 54}{space 4} .2036384{col 67}{space 3} .2747331
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R3
{txt}
{com}. regress att_index De4 if treatment == 4 & passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       202
{txt}{hline 13}{c +}{hline 34}   F(1, 200)       = {res}   139.56
{txt}       Model {c |} {res} 6.11501533         1  6.11501533   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 8.76300964       200  .043815048   {txt}R-squared       ={res}    0.4110
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.4081
{txt}       Total {c |} {res}  14.878025       201  .074020025   {txt}Root MSE        =   {res} .20932

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De4 {c |}{col 14}{res}{space 2} .3565401{col 26}{space 2} .0301801{col 37}{space 1}   11.81{col 46}{space 3}0.000{col 54}{space 4}  .297028{col 67}{space 3} .4160522
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}      .25{col 26}{space 2} .0188738{col 37}{space 1}   13.25{col 46}{space 3}0.000{col 54}{space 4} .2127829{col 67}{space 3} .2872172
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R4
{txt}
{com}. regress att_index De5 if treatment == 5 & passed == 1 & sample == 2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       220
{txt}{hline 13}{c +}{hline 34}   F(1, 218)       = {res}   111.71
{txt}       Model {c |} {res} 4.91703033         1  4.91703033   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 9.59543778       218   .04401577   {txt}R-squared       ={res}    0.3388
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3358
{txt}       Total {c |} {res} 14.5124681       219  .066266978   {txt}Root MSE        =   {res}  .2098

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   att_index{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}De5 {c |}{col 14}{res}{space 2} .3116303{col 26}{space 2} .0294844{col 37}{space 1}   10.57{col 46}{space 3}0.000{col 54}{space 4} .2535193{col 67}{space 3} .3697413
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2801418{col 26}{space 2} .0176683{col 37}{space 1}   15.86{col 46}{space 3}0.000{col 54}{space 4} .2453193{col 67}{space 3} .3149644
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. estimates store R5
{txt}
{com}. 
. coefplot R1 R2 R3 R4 R5, drop(_cons) vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.50)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4 0.5) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) offset(0.0) lcolor(black)
{res}{txt}
{com}. 
. *Affective polarization*
. 
. mean afpol_index if passed == 1, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}     1,715

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.afpol_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .2747592{col 43}{space 2} .0149347{col 54}{space 5} .2454671{col 68}{space 3} .3040513
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2} .3431676{col 43}{space 2}  .016644{col 54}{space 5} .3105229{col 68}{space 3} .3758124
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .3396842{col 43}{space 2} .0167716{col 54}{space 5} .3067892{col 68}{space 3} .3725791
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .3984038{col 43}{space 2} .0173772{col 54}{space 5} .3643209{col 68}{space 3} .4324866
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .3964995{col 43}{space 2} .0171658{col 54}{space 5} .3628314{col 68}{space 3} .4301676
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.40)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
. mean afpol_index if passed == 1 & sample == 1, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}       726

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.afpol_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .3259859{col 43}{space 2} .0253293{col 54}{space 5} .2762584{col 68}{space 3} .3757134
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2}  .422305{col 43}{space 2} .0283039{col 54}{space 5} .3667376{col 68}{space 3} .4778723
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .4243037{col 43}{space 2} .0270806{col 54}{space 5} .3711378{col 68}{space 3} .4774695
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .4638207{col 43}{space 2} .0251993{col 54}{space 5} .4143484{col 68}{space 3} .5132929
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .4712434{col 43}{space 2} .0304885{col 54}{space 5}  .411387{col 68}{space 3} .5310997
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.50)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4 0.5) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
. mean afpol_index if passed == 1 & sample == 2, over(treatment_group)
{res}
{txt}Mean estimation{col 52}Number of obs{col 68}= {res}       989

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 31}{c |}       Mean{col 43}   Std. Err.{col 55}     [95% Con{col 68}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
c.afpol_index@treatment_group {c |}
{space 13}Low_pol_and_civ  {c |}{col 31}{res}{space 2} .2391013{col 43}{space 2} .0178178{col 54}{space 5} .2041363{col 68}{space 3} .2740664
{txt}{space 13}Low_pol_and_inc  {c |}{col 31}{res}{space 2} .2876534{col 43}{space 2} .0193106{col 54}{space 5} .2497588{col 68}{space 3}  .325548
{txt}{space 12}High_pol_and_civ  {c |}{col 31}{res}{space 2} .2769712{col 43}{space 2} .0201332{col 54}{space 5} .2374626{col 68}{space 3} .3164799
{txt}{space 12}High_pol_and_inc  {c |}{col 31}{res}{space 2} .3376087{col 43}{space 2} .0231702{col 54}{space 5} .2921403{col 68}{space 3} .3830771
{txt}{space 21}Control  {c |}{col 31}{res}{space 2} .3501067{col 43}{space 2} .0197634{col 54}{space 5} .3113238{col 68}{space 3} .3888897
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. estimates store R1
{txt}
{com}. 
. coefplot R1, vertical recast(bar) barwidth(0.50) scheme(s1mono) fcolor(white) ciopts(recast(rcap) lcolor(black)) citop yscale(range(0 0.40)) xlabel(,angle(45)) ////
> ylabel(0 0.1 0.2 0.3 0.4) legend(off) addplot(scatter @b @at, ms(i) mlabel(@b) mlabpos(2) mlabcolor(black)) format(%9.2f) lcolor(black)
{res}{txt}
{com}. 
{txt}end of do-file

{com}. exit, clear
